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Emotions as infectious diseases in a large social network: The SISa model
Abstract
Human populations are arranged in social networks that determine interactions and influence the spread of diseases, behaviours and ideas. We evaluate the spread of long-term emotional states across a social network. We introduce a novel form of the classical susceptible-infected-susceptible disease model which includes the possibility for 'spontaneous' (or 'automatic') infection, in addition to disease transmission (the SISa model). Using this framework and data from the Framingham Heart Study, we provide formal evidence that positive and negative emotional states behave like infectious diseases spreading across social networks over long periods of time. The probability of becoming content is increased by 0.02 per year for each content contact, and the probability of becoming discontent is increased by 0.04 per year per discontent contact. Our mathematical formalism allows us to derive various quantities from the data, such as the average lifetime of a contentment 'infection' (10 years) or discontentment 'infection' (5 years). Our results give insight into the transmissive nature of positive and negative emotional states. Determining to what extent particular emotions or behaviours are infectious is a promising direction for further research with important implications for social science, epidemiology and health policy. Our model provides a theoretical framework for studying the interpersonal spread of any state that may also arise spontaneously, such as emotions, behaviours, health states, ideas or diseases with reservoirs.
... Emotions can spread like an infectious disease across social networks in a phenomenon called emotional contagion, which can be defined as a tendency to acquire affective states from our social contacts (Hatfield et al., 1994). For instance, the probability of an individual becoming "discontent" increases with the number of discontent contacts (Hill et al., 2010). This indicates that the social network is a potential source of both positive and negative emotions. ...
... This indicates that the social network is a potential source of both positive and negative emotions. Furthermore, emotional contagion seems to occur mostly between family members, partners, roommates, close friends, or co-workers that have strong ties and frequent contact (Bastiampillai et al., 2013;Hill et al., 2010). ...
... During social interaction, humans become aware of the other's sensations, emotions, and thoughts (Christakis and Fowler, 2013;Fowler and Christakis, 2009;Hill et al., 2010;Lundqvist and Dimberg, 1995;Prochazkova and Kret, 2017). Emotions such as embarrassment, shame, pride, and guilt are shared through cues such as facial and body expressions, gestures, posture, and sounds. ...
Contagious depression is a theory proposing that depression can be induced or triggered by our social environment. This theory is based on emotional contagion, the idea that affective states can be transferred during social interaction, since humans can use emotional contagion to communicate feelings and emotions in conscious and unconscious ways. This review presents behavioral, physiological, and neuroanatomical aspects of two essential contagious depression mechanisms, automatic mimicry and the mirror neuron system.
... Four decades of research on transmission of physiological stress among humans have established that responses to stressors exhibited by one person can be transmitted to another [28,37]. For instance, emotional reaction to stressors experienced in the work environment can propagate to partners, family and close friends, transmitting through social networks similarly to pathogens [38]. Although stronger social bonds are more receptive to transmission [39], stress responses can also be transmitted along weaker social links and among individuals unfamiliar with each other. ...
... A final major question is what form of transmission stress transmission takes. Although previously suggested to spread in similar ways to pathogens [38] (i.e. simple transmission), stress transmission probably has properties more similar to other forms of information transmission. ...
The stress systems are powerful mediators between the organism's systemic dynamic equilibrium and changes in its environment beyond the level of anticipated fluctuations. Over- or under-activation of the stress systems' responses can impact an animal's health, survival and reproductive success. While physiological stress responses and their influence on behaviour and performance are well understood at the individual level, it remains largely unknown whether—and how—stressed individuals can affect the stress systems of other group members, and consequently their collective behaviour. Stressed individuals could directly signal the presence of a stressor (e.g. via an alarm call or pheromones), or an acute or chronic activation of the stress systems could be perceived by others (as an indirect cue) and spread via social contagion. Such social transmission of stress responses could then amplify the effects of stressors by impacting social interactions, social dynamics and the collective performance of groups. As the neuroendocrine pathways of the stress response are highly conserved among vertebrates, transmission of physiological stress states could be more widespread among non-human animals than previously thought. We therefore suggest that identifying the extent to which stress transmission modulates animal collectives represents an important research avenue.
... Depression is a type of emotional disorder (29) and, according to the theory of emotional contagion, emotions, like infectious diseases, can spread through groups of people in social networks (30). Studies have found the effects of emotional contagion could be long term and profound. ...
... The disease can be transmitted to a susceptible person when they come into contact with an infected person. That means infection can only be contagious by having a contact of an infected and a susceptible individual (30). Extrapolating from the SIS model, we believe that teachers' depression may more easily transmit to students who are vulnerable to depression. ...
Background:
According to the theory of emotional contagion, emotions in one person can trigger similar emotions in groups within social networks. In schools, the class just like a small social network, that teachers' emotion, such as depression, might be contagious to their students. However, until now there is few studies reporting this issue. This study aims to explore whether teachers' depression be contagious to students and what mechanics behind the phenomenon.
Methods:
Using Children's depression and cognitive scales to assess 2,579 students, meanwhile using teachers' depression and emotional labor scales assess 529 teachers. The nested data from 112 classes were analyzed.
Results:
Teachers' depression was positively correlated with emotional labor surface and deep acting, and teachers' depression cross-level predicted students' depression inversely. For teachers with higher levels of depression, the teacher's deep acting affected their students' depression significantly, the more effortful the teachers' deep acting, the lower the degree of the students' depression, however, for teachers with lower levels of depression, the deep acting was not significant.
Conclusion:
The results maybe state that depression in teachers is not readily transmitted to students, one of reasons is that teachers' emotional labor may alleviate the influence of their depression on students. However, considered that teachers' emotional labor was positively correlated with their depression, the teachers' emotional labor may be like a double-edged sword, while alleviating the influence of teachers' depression on students, it also deteriorated their own depression, making it impossible sustainable. For students' depression interventions based in school, including teachers maybe a better selection.
... There are mainly two classes of traditional contagions: the susceptible-infected-susceptible (SIS) model and the susceptible-infected-recovered (SIR) model [21][22][23]. On this basis, combining a knowledge of psychology and sociology, these were applied to emotion modeling, which simulated the psychological state of individuals under an emergency, and widely used in the field of emotion contagion [24][25][26][27][28][29][30][31]. Hill et al., adopted the traditional SIS (susceptible-infected-susceptible) epidemiological model and data from the Framingham Heart Disease Research Center to illustrate that emotion can spread through social networks [24]. ...
... On this basis, combining a knowledge of psychology and sociology, these were applied to emotion modeling, which simulated the psychological state of individuals under an emergency, and widely used in the field of emotion contagion [24][25][26][27][28][29][30][31]. Hill et al., adopted the traditional SIS (susceptible-infected-susceptible) epidemiological model and data from the Framingham Heart Disease Research Center to illustrate that emotion can spread through social networks [24]. According to the susceptible-infected-susceptible (SIS) model, Zhao et al. studied that panic spreads in a subway emergency according to passenger density: characteristic of subway cars with confined spaces and passengers' psychological factors [25]. ...
Emotion plays an important role in decision making. In an emergency, panic can spread among crowds through person-to-person communications and can cause harmful effects on society. The aim of this paper is to propose a new theoretical model in the context of epidemiology to describe the spread of panic under an emergency. First, according to divisions in personality in the context of psychology, groups are divided into a level-headed group and an impatient group. Second, individuals in the two groups have unique personalities. Thus, the level-headed group only infects within the group, while the impatient group considers emotional infection within the group and cross infection between the groups. Then, a nonlinear infection rate is used to describe the probability of infection after an infected person contacts a susceptible person, which is more in line with the real situation. After that, the level-headed group–impatient group nonlinear SIRS panic spreading model is developed. Stable analysis of the model is obtained using the Lyapunov function method to study the stability of the panic-free equilibrium and panic-permanence equilibrium. Finally, simulations are carried out to dynamically describe the spread process of group emotional contagion.
... This loop and EC are accelerated by digital technology and social media. Social media makes it easier to express and communicate emotions and thus increases the receivers of EC (Dubey, 2020;Hill, 2010). ...
The Emotional Contagion Scale (ECS) developed by Dr. Elaine Hatfield, is a self-report measure used to investigate the individual’s susceptibility to catch another person’s emotions and experience the same. The catching of emotions could be conscious or unconscious. The study aims to validate the Emotional Contagion scale on the Indian subcontinent population for future use and application. The original American scale consisted of 15 items to be responded to by selecting the suitable option from given five, was given to an Indian sample of 498 individuals. To check the validity, Confirmatory Factor Analysis (CFA) was performed. Gender differences were assessed and it was observed that men were high on catching and experiencing the emotions of others as compared to women. The Indian sample on ECS shows moderate to high reliability and high content validity. It thus concludes that the Emotional Contagion scale is valid for future use on the Indian Population.
... Wang et al. (2015) simulated the emotional diffusion process of netizens in social networks utilizing the ESIS model and validated the model in both simulated and real networks. Hill et al. (2010) developed the SISa model by introducing the probability of "spontaneous infection" and utilizing actual data to determine the likelihood of specific emotional and behavioral contagion, thereby providing a theoretical framework for its research on interpersonal transmission. However, the current research does not account for the fact that emotions are transmitted through social network relationships between individuals, nor does it factor in the impact of individual emotional preferences and interactional differences on contagion results. ...
The optimization of the built environment is an indispensable course of action that needs to be rendered in an effort to enhance the lives of residents and advance urban development. However, the emotional expression of residents and the built environment exhibit a complex relationship. This study embeds an evolutionary game into the Agent simulation model, designs learning rules that integrate residents' personal preferences and historical information, and more accurately reflects the updating mechanism of residents' decision-making behavior in order to investigate the process of residents' emotion transmission in the event of China's community built environment transformation. Additionally, the regret theory is employed to enhance the model of how residents of real environments interact emotionally, followed by an analysis of the internal mechanisms underlying residents' emotional dynamic evolution under this complex relationship. The findings indicate that: (i) enhancing the propensity of neutral-emotion residents to interact with positive ones can promote the spread of positive emotions and system stability; (ii) moreover, residents' support costs, synergistic benefits, government compensation, and the difference between the information diffusion cost of residents holding negative and positive emotions influence the macroevolution of residents' emotional state; (iii) finally, current-limiting measures and government intervention can effectively restrain the spread of negative emotion, promote the spread of positive emotion, and the implementation time negatively impacts the control effect.
... Stress contagion refers to the transfer of a stressed state from one individual to another through observation or interaction. Emotional-contagion is a process that involves expressing and feeling the emotions that are similar to those of others [26]. Team leaders may benefit from being aware of the emotional dynamics of team members. ...
Mission teams are exposed to the emotional toll of life and death decisions. These are small groups of specially trained people supported by intelligent machines for dealing with stressful environments and scenarios. We developed a composite model for stress monitoring in such teams of human and autonomous machines. This modelling aims to identify the conditions that may contribute to mission failure. The proposed model is composed of three parts: 1) a computational logic part that statically describes the stress states of teammates; 2) a decision part that manifests the mission status at any time; 3) a stress propagation part based on standard Susceptible-Infected-Susceptible (SIS) paradigm. In contrast to the approaches such as agent-based, random-walk and game models, the proposed model combines various mechanisms to satisfy the conditions of stress propagation in small groups. Our core approach involves data structures such as decision tables and decision diagrams. These tools are adaptable to human-machine teaming as well.
... Homophily and social influence are both mechanisms for interpersonal altruistic behaviour, and both occur in social networks. There is evidence that emotions, thoughts, and behaviours can be spread through social network ties [21,22], and people's behaviour will be affected by their connections in social networks. In static networks, people's interaction objects are relatively fixed. ...
Trust is an important factor in human-robot interaction, it plays an important role in improving human acceptance of robots and building human-robot relationships. Today, when robots are more intelligent and the human-robot relationships is more intimate, the social attributes of robots and interaction scenarios are important factors affecting human-robot trust. Altruistic behaviour is a typical social behaviour, and reciprocity is a typical social interaction scenario. So, this study investigates the effects of reciprocity and robots’ altruistic behaviours on cognitive trust, emotional trust, behavioural trust and the mediating role of perceived intelligence. An experiment involving 42 participants was conducted. The virtual robots used in the experiment have three different behaviours: altruistic, selfish and control, and two interactive scenarios in the experiment: reciprocity and non-reciprocity. Participants in our study played the adapted Repeated Public Goods Game and the Trust Game with robot in two scenarios. The results indicate that robots’ altruistic behaviours significantly influence participants’ cognitive trust, emotional trust and behavioural trust, and reciprocity significantly influences only emotional trust and behavioural trust. Both robots’ altruistic behaviours and reciprocity positively influence perceived intelligence. Perceived intelligence mediates the effects of robots’ altruistic behaviours on cognitive and emotional trust and the effect of reciprocity on emotional trust. Implications are discussed for future work.
... These studies of social capital conceptualize the cohesiveness of networks in two ways: (1) the cohesiveness of a given individual's personal network (measured, for example, by the extent to which their friends are in turn friends with each other), and (2) the cohesiveness of the whole community (measured by the degree of fragmentation into subcommunities). Empirical studies have shown that these measures are associated with a range of outcomes, including the dynamics of various types of contagion [50][51][52][53][54][55][56][57] . Motivated by this literature, we construct three measures of social capital that characterize the structure of friendship links in a community. ...
Social capital—the strength of an individual’s social network and community—has been identified as a potential determinant of outcomes ranging from education to health1–8. However, efforts to understand what types of social capital matter for these outcomes have been hindered by a lack of social network data. Here, in the first of a pair of papers9, we use data on 21 billion friendships from Facebook to study social capital. We measure and analyse three types of social capital by ZIP (postal) code in the United States: (1) connectedness between different types of people, such as those with low versus high socioeconomic status (SES); (2) social cohesion, such as the extent of cliques in friendship networks; and (3) civic engagement, such as rates of volunteering. These measures vary substantially across areas, but are not highly correlated with each other. We demonstrate the importance of distinguishing these forms of social capital by analysing their associations with economic mobility across areas. The share of high-SES friends among individuals with low SES—which we term economic connectedness—is among the strongest predictors of upward income mobility identified to date10,11. Other social capital measures are not strongly associated with economic mobility. If children with low-SES parents were to grow up in counties with economic connectedness comparable to that of the average child with high-SES parents, their incomes in adulthood would increase by 20% on average. Differences in economic connectedness can explain well-known relationships between upward income mobility and racial segregation, poverty rates, and inequality12–14. To support further research and policy interventions, we publicly release privacy-protected statistics on social capital by ZIP code at https://www.socialcapital.org. Analyses of data on 21 billion friendships from Facebook in the United States reveal associations between social capital and economic mobility.
... Multiple methods and approaches have been designed to study the spread of diseases and opinion according to the situation and amount of information available. More recently, these models have been used to study a variety of social contagion including obesity [43], emotions [44], alcoholism [45,46], substance abuse [47], information spreading [48] to name a few. Due to the similarity of spread of smoking behaviour to other social contagion, we can use insights from these fields to develop models. ...
Over the years, population-level tobacco control policies have considerably reduced smoking prevalence worldwide. However, the rate of decline of smoking prevalence is slowing down. Therefore, there is a need for models that capture the full complexity of the smoking epidemic. These models can then be used as test-beds to develop new policies to limit the spread of smoking. Current models of smoking dynamics mainly use ordinary differential equation (ODE) models, where studying the effect of an individual's contact network is challenging. They also do not consider all the interactions between individuals that can lead to changes in smoking behaviour, implying that they do not consider valuable information on the spread of smoking behaviour. In this context, we develop an agent-based model (ABM), calibrate and then validate it on historical trends observed in the US and UK. Our ABM considers spontaneous terms, interactions between agents, and the agent's contact network. To explore the effect of the underlying network on smoking dynamics, we test the ABM on six different networks, both synthetic and real-world. In addition, we also compare the ABM with an ODE model. Our results suggest that the dynamics from the ODE model are similar to the ABM only when the network structure is fully connected (FC). The FC network performs poorly in replicating the empirical trends in the data, while the real-world network best replicates it amongst the six networks. Further, when information on the real-world network is unavailable, our ABM on Lancichinetti-Fortunato-Radicchi benchmark networks (or networks with a similar average degree as the real-world network) can be used to model smoking behaviour. These results suggest that networks are essential for modelling smoking behaviour and that our ABM can be used to develop network-based intervention strategies and policies for tobacco control.
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
Thanks to improvements in living standards and health behavior as well as medical progress since the second half of the twentieth century, old age has become a life phase in its own right. This phase usually begins by the transition from working life to retirement (Kohli, 2000). Both the chance of reaching retirement and the life expectancy after retirement have increased significantly (Eisenmenger & Emmerling, 2011). The post-work phase spans several decades for many people now. In addition, people who retire are considerably healthier and more independent than their peers of earlier birth cohorts (Crimmins, 2004). The expansion of this phase of life has been accompanied by a differentiation of older people in terms of health and independence: healthy and active people experience this phase, as do people in need of help and care. This fact is considered by distinguishing between old and very old people (Baltes, 2007). Characteristics of old age are absence of non-compensable health restrictions, self-determination of various activities (e.g., traveling, hobbies, voluntary work), and strong social integration. Overall, the demands of old age can be coped well in this phase. Very old age is characterized by an increase in physical and cognitive losses and diseases, and a decrease in the abilities and possibilities of compensating for deficits (Baltes, 1997; Baltes & Smith, 2003).
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
“Tell me how much your friends earn and I’ll tell you whether you smoke, what diseases you have and how old you’re going to become!” Part of this statement should be familiar to those who are interested in the connection between social inequality and health. People of comparatively lower socioeconomic status are at higher risk of health problems and are more likely to fall ill and die earlier than those who have a higher income etc. However, the sentence does not ask about your own income, but about the income of your friends. Is this information really meaningful? Does it really make a difference to your own health which friends you have, who you surround yourself with in your everyday life and what social position these people have?
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
This chapter summarizes the current state of research on social status, social relations, and health. The focus is on two questions: (1) Is there evidence of an explanatory contribution of social relationships on the association of social status and health (mediating effect of social relationships), and (2) do associations of social relations and health vary in different social status groups (moderating effect of social status)? There is evidence that social relationships can help explain health inequalities. The current state of research on the moderating effect is less clear. Although there are indications of a moderating effect, the results for both questions vary greatly regarding indicators used for social relationships or health. Research on these questions has so far neglected a more complex measurement of social relations, such as in social networks. Complex assessments of social relations might help in finding more detailed insights.
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
Since 1960s school-based surveys also focused on social networks of young people. In comparison with other life stages, the evidence regarding social network research is more advanced for school-aged children. These studies identified that homophile of peer groups in adolescence can be attributed to two mechanisms: the thesis of social influence (young people adapt to health and health behaviour of their friends) and the thesis of selection (adolescents choose their friends according to whether they show the same attitudes and (health) behavior as they do themselves). The existing studies focused especially on substance use (smoking and drinking) but also on physical activity and nutrition and to a lesser extent also on mental health, where both these are relevant. However, for explaining health inequalities the evidence is scarce. This chapter will give an overview of social network research on young people and will give insights into the few existing studies regarding the explanation of health inequalities in adolescence (especially regarding smoking). It will also emphasize the need for further research in explaining health inequalities (beyond tobacco consumption) as well as longitudinal research designs.
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
In this chapter we deal with the health and inequality aspects of networks from a psychological and sociological life span perspective. In doing so, we pay attention to the mutual interactions between health, social inequality, and networks in the context of biographical transitions that decisively shape the life course of adults. We focus exclusively on young and middle adulthood—here roughly defined as the age span between 20 and 60 years. We introduce the disciplinary perspectives and paradigms that deal with the topic of networks and health inequalities in different phases of life. We present theories that describe interactions between these concepts, and we summarize the state of research on the relationships between social and health inequalities, networks and health, and inequalities, networks, and health. We conclude with a summary and some desiderata for future research.
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
The loss of employment is an event that interferes with the lives of everyone affected, causes stress, and can have a negative impact on their health. Meta-analyses show that unemployed people have a worse state of health and a mortality risk that is at least 1.6 times higher than those who are employed. Unemployment is associated with a lower mental and physical health status and, in some cases, with riskier health behavior (particularly tobacco consumption). There are two important theses on the role of social networks in this context: (1) Unemployment changes social networks so that they no longer fulfill their positive function for health (mediator thesis); (2) Unemployment leaves social networks unchanged and persons with resource-rich networks suffer less from health losses due to unemployment (moderator thesis). This article provides an overview of empirical analyses on the topic of networks and unemployment.
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
This article reviews literature on social network effects on children's health. Regarding structural aspects, it can be seen that social networks for children consist in the inner circle mainly of members of the core family (parents, siblings) and in the extended circle of other family members such as grandparents and friends. Network size and the proportion of friends in the network increase with the age of the children. With regard to network effects on health it becomes clear that child health is influenced directly by the child’s social network as well as indirectly by the social network of the parents. Of the various theoretical mechanisms that can be used to explain these findings —for example, social support, social contagion, or social control—the support mechanism is best empirically confirmed. Furthermore, it is consistently shown that family social capital correlates positively with the socioeconomic resources of parents in Western industrialized countries. In emerging and developing countries, it is apparent that children’s health is increasingly dependent on the availability of social support.
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
The influence and significance of social networks in health research are becoming widely discussed. Sociological network research meets the demand for a stronger consideration of “contexts” or the “environment” that influences health and care. Social networks are conceived as a mediating meso-level, which mediates between social macro-structures (e.g., healthcare systems, institutions, and organizations) and individual (not always) rationally acting actors. This perspective offers the possibility to analyze a variety of psychosocial mechanisms. These mechanisms can influence individual health in different ways, including (health) behavior, psyche, or physiology. In this chapter we present some central theoretical concepts, as well as empirical results, on network effects under the headings of “social support,” “social integration,” “social influence,” and “social contagion.”
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
“Tell me how much your friends earn, and I’ll tell you if you smoke, what diseases you have and how long your life will be!” With this somewhat pointed statement, we wanted to shed light on the empirically well-confirmed connection between social and health inequalities from the perspective of network research at the beginning of this book (see chapter “Social networks and health inequalities: a new perspective for research”). Social networks are understood here as mediating entities at an intermediate or meso-level, whose structure and function mediate between vertical (income, education, occupational status, etc.) as well as horizontal (e.g., age, gender, ethnic origin) inequalities and health inequalities (e.g., life expectancy, morbidity rates). Besides this mediating influence a moderating relationship wherein social networks amplify or diminish vertical and horizontal inequalities seems to be reasonable.
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
There are significant differences in morbidity (incidence of disease) and mortality (death rate) between men and women. By puberty, male adolescents are more likely to have health problems. During puberty, girls suffer from chronic and mental illnesses and male adolescents are more likely to suffer from acute and life-threatening diseases. Boys and men have riskier health behavior. The field of research mainly relates to the binarity of the sexes—men and women. Studies on trans and queer persons are rare in this field. Networks have a gender-specific effect on risk behavior. Women provide more and more time-consuming social support, even in case of illness. After widowhood, networks have both negative and positive effects, which are gender-specific.
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
Negative ties are essential components of social networks. The central task of the present chapter is to elicit the state of research on the contribution of negative ties to the reproduction of health inequalities. In the first step, we elaborate on commonalities and differences regarding the understanding of negative ties. Subsequently, we take a look at the relationship between negative ties and some health parameters in the field of physical and mental health as well as health behaviours. Furthermore, we explore the thesis that socioeconomic status and negative ties are related to one another. We conclude with an outlook where we address the main desiderata for research on negative ties and inequalities in health.
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
Over the past decades single parent households have become established in most OECD countries. Single parenting comes with specific risks: single parents bear a higher poverty risk and have worse mental and physical health than married parents. While the relevance of social relations and support for well-being and health has been widely documented, networkanalytical studies are rare in this field. However, they promise new insights into how social network structures, different types of relations and different kinds of interactions impact single parents’ health.
... The mechanisms of emotional contagion and imitation are placed in a context of rather short-lived and concrete social situations (e.g., a cheering concert audience), but there is evidence that longer-lasting emotional states, such as happiness or loneliness, also spread in social networks (Cacioppo et al., 2009;Hill et al., 2010). Martin and DiMatteo (2017) ...
Social relations lie at the core of sociology; they are basically its framework. Without social relations, no social interactions develop. The study of social relations looks back on a long tradition of research, and this tradition is continuing in constantly differentiating and specializing subsystems. The aim of this chapter is to give a brief overview of research traditions on social relations. In particular, it aims to clarify and, where possible, differentiate between concepts that have been developed in the course of research on social relations in sociology and other related disciplines (such as social psychology). Why is a classification necessary? When dealing with research on social relations, it can be observed that different terms are used synonymously and that originally intended demarcations between them blur over time. This chapter addresses the following questions: What terms are used in sociological research on social relations? How are they defined? And how can an overarching concept of social networks emerge from these different terms?
... The study found that the negative emotions on Twitter are related to a lower transmission rate of the corresponding susceptible compartment . Hill et al. (2010) assessed the spread of emotions in social networks through the SISa model and proved that both positive and negative emotions can exist in social networks for a long time like infectious diseases. The research on the spread of emotions in the crowd is also worthy of reference. ...
In the context of the COVID-19 pandemic, a large amount of information is gathered on Internet platforms, through which people express their opinions and vent their emotions. Emotional guidance of netizens has become an important part of social governance during turbulences caused by a so-called “infodemic”. This study focuses on the evolution and interaction of netizens' emotions after the occurrence of network public opinion events. First, the transfer model of netizens' emotions is constructed, and the significance of each parameter in the model is studied through simulation. Then, based on the model, we put forward the optimization method and quantitative method of guidance strategy of netizens' emotions. Finally, the empirical study proves the effectiveness of the model, which can provide a theoretical basis for the emotional guidance strategies after the outbreak of network public opinion events.
... Once the process converges to the absorbing state, the process jumps to a randomly selected sample from the history of the SIS process. Keeling and Ross [11] and Hill et al. [12] introduced a self-infection process ε on the complete graph. In addition to the usual infection and curing processes, the nodes in the modified process can be infected by external sources, which are modeled as self-infections. ...
We analyze continuous-time Markovian ϵ-SIS epidemics with self-infections on the complete graph. The majority of the graphs are analytically intractable, but many physical features of the ϵ-SIS process observed in the complete graph can occur in any other graph. In this work, we illustrate that the timescales of the ϵ-SIS process are related to the eigenvalues of the tridiagonal matrix of the SIS Markov chain. We provide a detailed analysis of all eigenvalues and illustrate that the eigenvalues show staircases, which are caused by the nearly degenerate (but strictly distinct) pairs of eigenvalues. We also illustrate that the ratio between the second-largest and third-largest eigenvalue is a good indicator of metastability in the ϵ-SIS process. Additionally, we show that the epidemic threshold of the Markovian ϵ-SIS process can be accurately approximated by the effective infection rate for which the third-largest eigenvalue of the transition matrix is the smallest. Finally, we derive the exact mean-field solution for the ϵ-SIS process on the complete graph, and we show that the mean-field approximation does not correctly represent the metastable behavior of Markovian ϵ-SIS epidemics.
... Our simulations show that, overall, mothers were more likely to be depressed if they removed a depressed friend from their social network. This is surprising considering that most, albeit not all [75], existing evidence has shown that depression is socially contagious [76][77][78]. However, these results ultimately show that increases to social networks are beneficial and reduce the likelihood of a mother having depression, whether or not persons in that social network are depressed. ...
Depression is a major public health concern among expectant mothers in Canada. Income inequality has been linked to depression, so interventions for reducing income inequality may reduce the prevalence of maternal depression. The current study aims to simulate the effects of government transfers and increases to minimum wage on depression in mothers. We used agent-based modelling techniques to identify the predicted effects of income inequality reducing programs on maternal depression. Model parameters were identified using the All Our Families cohort dataset and the existing literature. The mean age of our sample was 30 years. The sample was also predominantly white (78.6%) and had at least some post-secondary education (89.1%). When income was increased by just simulating an increase in minimum wage, the proportion of depressed mothers decreased by 2.9% (p < 0.005). Likewise, simulating the Canada Child Benefit resulted in a 5.0% decrease in the prevalence of depression (p < 0.001) and Ontario’s Universal Basic Income pilot project resulted in a simulated 5.6% decrease in the prevalence of depression (p < 0.001). We also assessed simulated changes to the mother’s social networks. Progressive income policies and increasing social networks are predicted to decrease the probability of depression.
... Also in the region of social physics, a methodology to positively take the emotion into account as a variable has been accepted where the action and the way of thinking of people are treated in terms of the emotion [15][16][17][18][19][20][21][22]. In these approaches the emotion is usually introduced as a function of other variables or treated as a parameter normalized within [0, 1], for instance. ...
A strong field of negative information as the case realized by COVID-19 must greatly enhance the public feelings such as the fear, the disgust and a sense of crisis against it. The information environment regarding COVID-19 and the public reactions to it, which had appeared from the early 2020 to September 2021 in Japan, were first reviewed. The proposition of a mathematical model was followed, where the negative and strong field of information as the issue of COVID-19 was assumed to make the public surprised and their emotions changed negatively via the mechanism of emotional contagion. The frequency of the public access to SNS and Internet under the atmosphere of COVID-19 was considered as a manifestation of the public for seeking reliable information and as an index of the public reaction originated from the negative emotion. By using the time-varying data of the information field of COVID-19, the extent of the public surprise that was considered as the emotional contagion from the field was derived. That extent became clear to have varied heterogeneously with time, having been subjected by the state of information field which have varied with three phases as the initial, transient and quasi-stable ones. It was found that, only in the quasi-stable state of the field, the number of public access to SNS and Internet can mimic the social reality of the issue concerned. Physical and mathematical models, where the psychological phenomena as the emotional contagion are positively included, were pointed out to be central ingredients to understand the behavior of the public in the society more comprehensively than it is today. INTRODUCTION All the news media such as newspapers and the television make information environment around us. Since people live in such an environment [1,2], they are aware of negative or positive atmospheres of the environment so that they become to be of the same color as the environment though it may be temporary. The sense of people on a certain subject is, thus, determined depending on the quality and the strength of the information environment so that the time variation of the collective sense of people can be said to link with the variation of the information environment through the mechanism of emotional contagion [3-5].
... A study in PNAS collected over three million posts on Facebook from 698,003 users over a 20-year period and found that emotion could be transferred to others through emotional contagion, causing people to experience the same emotions unconsciously [25]. These positive and negative emotional states were proven to "behave like infectious diseases spreading across social networks over a long period of time" [26]. Negative emotional contagion, that is, catching someone else's bad mood and experiencing an increase in negative mood as a result, is particularly common in ODCs. ...
Disease-specific online health communities provide a convenient and common platform for patients to share experiences, change information, provide and receive social support. This study aimed to compare differences between online psychological and physiological disease communities in topics, sentiment, participation, and emotional contagion patterns using multiple methods as well as to discuss how to satisfy the users' different informational and emotional needs. We chose the online depression and diabetes communities on the Baidu Tieba platform as the data source. Topic modeling and theme coding were employed to analyze discussion preferences for various topic categories. Sentiment analysis was used to identify the sentiment polarity of each post and comment. The social network was used to represent the users' interaction and emotional flows to discover the differences in participation and emotional contagion patterns between psychological and physiological disease communities. The results revealed that people affected by depression focused more on their symptoms and social relationships, while people affected by diabetes were more likely to discuss treatment and self-management behavior. In the depression community, there were obvious interveners spreading positive emotions and more core users in the negative emotional contagion network. In the diabetes community, emotional contagion was less prevalent and core users in positive and negative emotional contagion networks were basically the same. The study reveals insights into the differences between online psychological and physiological disease communities, providing a greater understanding of the users' informational and emotional needs expressed online. These results are helpful for society to provide actual medical assistance and deploy health interventions based on disease types.
... Emotions expressed by others in social media affect the individual's moods through emotional contagion (Kramer, Guillory, & Hancock, 2014). Scholars have argued that social media accelerate emotional contagion (Hill et al. 2010). ...
Increasing depression and mental health problems among the elderly during the pandemic have become a grave concern. In the present study, we borrowed from the emotional contagion theory and examined the association between social media use (SMU) and depression among the elderly during the pandemic. Our findings suggest that active but not passive SMU is positively related to depression. Moreover, we also examined if SMU (both active and passive) has a varying effect on the mental health of the elderly based on their race, i.e., blacks and whites. Our findings suggest that active SMU is detrimental for both blacks and whites, whereas passive SMU is positively related to depression only among blacks. Further, we undertook multiperiod analyses where depression scores were measured at four different time periods. We found that the adverse impact of SMU on depression persists over time. The present study draws attention to the antecedents of depression among the elderly during COVID-19. Implications for theory and practice are discussed.
... While the emotion contagion effect has been well established in offline interpersonal communication context (e.g., Pugh, 2001), recent studies have also provided evidence for the same effect in online settings where non-verbal cues are absent. That is, emotions spread from message creators to message receivers through social networks in various contexts (e.g., Hill et al., 2010). For example, Huffaker (2010) focused on user interaction in online discussion forums and found that when users expressed certain emotions in their messages, other users were more likely to express the same emotions in their replies to the user. ...
This study investigated nonprofit organizations’ (NPOs) emotion-based content strategies on Facebook and publics’ engagement behaviors. More than 52,000 Facebook posts and corresponding comments were collected from the top 100 NPOs in the United States. The emotion-carrying status and valence of the messages were analyzed with computer-assisted sentiment analysis procedures. Results confirmed emotion-carrying posts and posts with negative emotions led to increased public engagement as indexed by the volumes of likes, shares, and comments. The presence of emotions and valence of the NPOs’ posts were also found to have a diffusion effect on user comments.
... Most of them mainly rely on the user's own emotional development rules, while ignoring the neighbors' effect on the user's emotion. In fact, the way in which users share their emotions online affects not only their own emotions [7], but also the emotions of others with whom they relate [8]. Furthermore, Bond et al. [9] find that strong ties are instrumental in spreading individual emotions both in the online and practical world. ...
The future emotion prediction of users on social media has been attracting increasing attention from academics. Previous studies on predicting future emotion have focused on the characteristics of individuals’ emotion changes; however, the role of the individual’s neighbors has not yet been thoroughly researched. To fill this gap, a surrounding-aware individual emotion prediction model (SAEP) based on a deep encoder–decoder architecture is proposed to predict individuals’ future emotions. In particular, two memory-based attention networks are constructed: The time-evolving attention network and the surrounding attention network to extract the features of the emotional changes of users and neighbors, respectively. Then, these features are incorporated into the emotion prediction task. In addition, a novel variant LSTM is introduced as the encoder of the proposed model, which can effectively extract complex patterns of users’ emotional changes from irregular time series. Extensive experimental results show that the proposed approach outperforms five alternative methods. The SAEP approach has improved by approximately 4.21–14.84% micro F1 on a dataset built from Twitter and 7.30–13.41% on a dataset built from Microblog. Further analyses validate the effectiveness of the proposed time-evolving context and surrounding context, as well as the factors that may affect the prediction results.
... Information and emotions spread in social networks similarly to pathogens [55]. Based on the three elements of epidemic transmission [56]-infection sources, transmission routes, and susceptible population-we divided the process of emotional contagion into three elements-emotional interaction information, interactive behavior, and susceptible group-and then analyzed these elements to promote positive emotional contagion and reduce negative emotional contagion. ...
Negative emotions are prevalent in the online depression community (ODC), which potentially puts members at risk, according to the theory of emotional contagion. However, emotional contagion in the ODC has not been confirmed. The generalized estimating equation (GEE) was used to verify the extent of emotional contagion using data from 1548 sample users in China’s popular ODC. During interaction, the emotional themes were analyzed according to language use. The diurnal patterns of the interaction behaviors were also analyzed. We identified the susceptible groups and analyzed their characteristics. The results confirmed the occurrence of emotional contagion in ODC, that is, the extent to which the user’s emotion was affected by the received emotion. Our study also found that when positive emotional contagion occurred, the replies contained more hopefulness, and when negative emotional contagion occurred, the replies contained more hopelessness and fear. Second, positive emotions were easier to spread, and people with higher activity in ODC were more susceptible. In addition, nighttime was an active period for user interaction. The results can help community managers and support groups take measures to promote the spread of positive emotions and reduce the spread of negative emotions.
... In recently decades, further studies on mathematical analysis of such a SIS reaction-diffusion equation with varying total population (linear source or logistic source) have been investigated by [12,26,27,38], their results indicate that varying total population can enhance disease persistence. Recently, in [18,19], Hill et al. adapted the classic epidemic model to describe the effect of spontaneous infection mechanism by adding a term whereby uninfected populations spontaneously (or "automatically") become infected independent of infected contacts. The "spontaneous factors" means that the spread of infectious diseases will be not only transmitted by direct contract between the susceptible and infected population but also the effect of spontaneous infection (spontaneous social infection in addition to disease transmission, such as, emotions, behaviors or ideas). ...
In this paper, we are concerned with a reaction-diffusion SIS epidemic model with saturated incidence rate, linear source and spontaneous infection mechanism. We derive the uniform bounds of parabolic system and obtain the global asymptotic stability of the constant steady state in a homogeneous environment. Moreover, the existence of the positive steady state is established. We mainly analyze the effects of diffusion, saturation and spontaneous infection on the asymptotic profiles of the steady state. These results show that the linear source and spontaneous infection can enhance the persistence of an infectious disease. Our mathematical approach is based on topological degree theory, singular perturbation technique, the comparison principles for elliptic equations and various elliptic estimates.
... Inversely, incorporating information about a user's influence based on network topology has been used to augment sentiment analysis [128,125]. Furthermore, contagion models have been developed to study how emotion and emotive content propagates and diffuses throughout social networks; sentiment in social media-based content has been shown to correlate with both the speed and quantity of information sharing [129,130,121,123]. ...
The coexistence of diverse opinions is necessary for a pluralistic society in which people can confront ideas and make informed choices. The media functions as a primary source of information, and diversity across news sources in the media forms the basis for wider discourse in the public. However, due to numerous economic and social pressures, news sources frequently co-orient their content through what is known as intermedia agenda-setting. Past research on the subject has examined relationships between individual news sources. However, to understand emergent behaviour such as opinion diversity, we cannot simply analyse individual relationships in isolation, but instead need to view the media as a complex system of many interacting entities. The aim of this thesis is to develop and empirically test a method for understanding the network effects that intermedia agenda-setting has on the diversity of expressed opinions within the media. Utilising latent signals extracted from news articles, we put forward a methodology for inferring networks that capture how agendas propagate between news sources via the opinions they express on various topics. By applying this approach to a large dataset of news articles published by globally and locally prominent news organisations, we identify how the structure of intermedia networks is indicative of the level of opinion diversity across various topics. We then develop a theoretical model of opinion dynamics in noisy domains that is motivated by the empirical observations of intermedia agenda formation. From this, we derive a general analytical expression for opinion diversity that holds for any network and depends on the network's topology through its spectral properties alone. Finally, we validate the analytical expression in a linear model against empirical data. This thesis aids our understanding of how to model emergent behaviour of the media and promote diversity.
... The second point to be noticed is that the definitive method such as traditional BCM model can not be applied when the fuzzy environment of information exerts on the fuzzy state of public opinion. The public attitude and opinion will be varied under the influence of emotional contagion of the information environment that is vague and fuzzy [15][16][17][18][19][20]. Hence the fuzzy theory [21,22] may possibly be introduced in treating the opinion dynamics. ...
... Studies show that users' emotions (Hill et al., 2010(Hill et al., , 2015, depressive behavior , and loneliness (Cacioppo et al., 2009) can be transmitted through social connections. Hence, leveraging social relationships between users can contextualize potential suicidal intent (Mueller and Abrutyn, 2015;Burnap et al., 2015;Colombo et al., 2016). ...
... A line of recent research using computational sentiment analysis on Twitter data found that sentiment, as determined by the presence of key words, significantly increases retweeting behavior (Kim & Yoo, 2012). Messages that contain emotional states tend to be circulated through different networks (Hill et al., 2010). This suggests that tweets labeled as having emotion tend to be retweeted more. ...
Using a year's worth of tweets related to climate change, we looked at the emotional content of messages that climate change deniers posted and engaged with through retweeting. The results of content analysis show that climate change deniers posted only 11% of our tweets and that most were negatively emotion-laden, with anger and sarcasm overwhelmingly present. Our findings shed light on the roles of emotions-particularly anger-in the posting and engagement though retweets, of climate messages on Twitter.
Individual and community psychology plays an important role in disaster management as human behavior exhibit diverse risk perceptions, recognition of the threats that exists, positive and negative emotions, panic, anger, rumor, stress and learned helplessness. These psychological factors are important as lack of attention to these can lead to detrimental outcome of disaster management effort. Disaster psychology has been seen as an emerging area of research and practice which deals with understanding of the psychological impact of individuals and community aftermath of the disasters. The aim of this paper is to put forward the conceptualization and development of dynamic networked psychology as a theoretical framework and its implications in exploring emotional contagion during disasters. We advocate theories of structural network dynamics can be used to construct DNP for exploring individuals as well as community coping mechanisms for improving preparedness, response and recovery of disasters. The advent of computational social science promotes the empirical modelling and analysis of massive volume of user data by inferring meaningful patterns for finding answers to important social and behavioral science research questions dealing with individual and community coping ability. In presenting a theoretical framework, we suggest that the underlying assumptions and integration of theories of social influence can be used to explore networks of emotional contagion for disasters.
The emotions of individuals are one of the most important factors for affecting cooperation in human society. An individual’s acceptability of her/his own strategy, as one kind of powerful emotion that can be influenced by the neighbors’ strategies, can prompt the individual to adjust her/his strategy in the evolution process of a spatial game. Based on this fact, a spatial prisoner’s dilemma game with acceptability involved is studied in this paper. The average acceptability in the community is introduced to the individual’s fitness in the model. The numerical experiments show that individuals considering average acceptability can greatly facilitate cooperation under certain conditions. Furthermore, when the temptation value is small, rational individuals to blind conformity behavior can promote cooperative behavior, but for a high temptation value, rational individuals are not conducive to cooperation. These results may offer insights to comprehensively understand the mechanism of emotion promoting cooperation.
The present study examines how contextual age discrimination moderates the individual-level association between perceived age discrimination and happiness among older Europeans. In this endeavor, we test two opposing views: 1) the “social norm” hypothesis that predicts the association between perceived age discrimination and happiness to become weaker in areas with a higher average level of age discrimination; and 2) conversely the “contagion effect” hypothesis that predicts the association to grow stronger in such areas. Using data from the European Social Survey (2008), we estimate two- and three-level mixed effects models to test these opposing hypotheses. Our findings from multilevel analysis lend support to the social norm hypothesis. Specifically, the negative link between perceived age discrimination and happiness is weaker in subnational regions where the proportion of victims of age discrimination is higher.
In this paper, we investigate the effect of spontaneous infection and advection for a susceptible-infected-susceptible epidemic reaction-diffusion-advection model in a heterogeneous environment. The existence of the endemic equilibrium is proved, and the asymptotic behaviors of the endemic equilibrium in three cases (large advection; small diffusion of the susceptible population; small diffusion of the infected population) are established. Our results suggest that the advection can cause the concentration of the susceptible and infected populations at the downstream, and the spontaneous infection can enhance the persistence of infectious disease in the entire habitat.
This chapter reflects on some of the ways in which microMicroand macroMacro discourses interact with one another in society, both creating and perpetuating dominant ways of meaning-making that are culturally, historically, and politically mediated. We focus particularly here on the creation and sustainability of dominant discourses in relation to the concept of risk.
Bursts and collective emotion have been widely studied in social physics field where researchers use mathematical models to understand human social dynamics. However, few researches recognize and separately analyze the internal and external influence on burst behaviors. To bridge this gap, we introduce a non-parametric approach to classify an interevent time series into five scenarios: random arrival, endogenous burst, endogenous non-burst, exogenous burst and exogenous non-burst. In order to process large-scale social media data, we first segment the interevent time series into sections by detecting change points. Then we use the rule-based algorithm to classify the time series based on its distribution. To validate our model, we analyze 27.2 million COVID-19 related comments collected from Chinese social media between January to October 2020. We adopt the emotion category called Profile of Mood States which consists of six emotions: Anger, Depression, Fatigue, Vigor, Tension and Confusion. This enables us to compare the burst features of different collective emotions during the COVID-19 period. The burst detection and classification approach introduced in this paper can also be applied to analyzing other complex systems, including but not limited to social media, financial market and signal processing.
Negative emotional contagion along with sentiment mutation through information propagation on social media is critical for mitigating disinformation and directing public opinion for compliance with key public interventions, such as vaccine uptake during a pandemic. Here, we develop a dynamic multiple negative emotional susceptible-forwarding-immune (MNE-SFI) model to examine how negative emotion spreads on social media and how sentiment mutation impacts by fitting the model to real multiple temporal information in messages with sentiments obtained from the Chinese Sina microblog. Emotional choices, meaning that individuals attempting to spread information are not only influenced by the objective emotions embedded in the influential information spread by influencers but also by subjective emotional tendencies, is an essential human behavior for information propagation. Hence, we seek to link the negative emotional contagion in the network at the macroscopic level to the emotional choices of individuals, and model parameters are used at the microcosmic level to measure the “copying” and “mutation” probabilities of negative sentiments in an event. Our results illustrate the emotional choices of users play essential roles in methods for mitigating harmful emotion spread and promoting meaningful emotion diffusion.
Kensbock, Alkærsig, and Lomberg (KAL) (2022) address the important topic of employee mental health in organizations. For three reasons, we caution readers against embracing KAL’s proposition that employee mobility spreads mental disorders across organizations through a contagion process. First, we view harmful contagion as the least plausible of three theoretical mechanisms that imply similar empirical results. Second, despite detailed employment and healthcare data from Denmark, the empirical analysis does not distinguish harmful contagion from the alternative mechanisms. Third, KAL’s infectious disease metaphor and language risk further stigmatization of vulnerable populations with mental disorders. We offer suggestions for continuing research on healthy organizations.
In this paper, we propose a reaction-diffusion-advection SIS epidemic model with linear external source to study the effects of open advective environments on the persistence and extinction of infectious diseases. Threshold-type results on the global dynamics in terms of the basic reproduction number \begin{document}$ \mathcal{R}_{0} $\end{document} are established. It is found that the introduction of open advective environments leads to different monotonicity and asymptotic properties of the basic reproduction number \begin{document}$ \mathcal{R}_0 $\end{document} with respect to the diffusion rate \begin{document}$ d_I $\end{document} and advection speed \begin{document}$ q $\end{document}. Our analytical results suggest that increasing the advection speed or decreasing the diffusion rate of infected individuals helps to eradicate the diseases in open advective environments.
Addiction is a complex biopsychosocial phenomenon, impacted by biological predispositions, psychological processes, and the social environment. Using mathematical and computational models that allow for surrogative reasoning may be a promising avenue for gaining a deeper understanding of this complex behavior. This paper reviews and classifies a selection of formal models of addiction focusing on the intra- and inter-individual dynamics, i.e., (neuro)psychological models and social models. We find that these modeling approaches to addiction are too disjoint and argue that in order to unravel the complexities of biopsychosocial processes of addiction, models should integrate intra- and inter-individual factors.
When emergencies occur, negative emotional contagion produced in crowds makes people irrational, resulting in stampedes and crushes. The intervention of crowd emotional contagion is an efficient method for avoiding serious accidents and ensuring the safety of people’s lives and properties. However, it is a challenging problem to provide an optimized intervention scheme for crowd emotional contagion because the appropriate intervention intensity is hard to achieve, e.g., too little intervention cannot restrain the outbreak of emotion, while excessive intervention will lead to the waste of manpower and material resources. Moreover, stochastic evolutionary characteristics of emotional contagion have further aggravated this problem since it is difficult to describe the stochastic changes in emotional contagion accurately. To solve this problem, we propose an intervention optimization scheme for crowd emotional contagion to maximize the number of uninfected individuals while minimizing the intervention cost. First, we construct a stochastic event-based emotional contagion (SEEC) model to capture the stochastic evolution characteristics of emotional contagion. Based on SEEC, we then propose a Hawkes process-based intervention (HPI) model to quantify the intervention intensity. Next, we formulate the intervention optimization as a problem of maximizing the ratio of the expected number of individuals being intervened to the cost of manual intervention. Finally, we propose an intervention optimization-artificial bee colony (IO-ABC) algorithm to heuristically solve the optimization problem. The experimental results show that our method can effectively intervene in emotional contagion.
In this paper, I attempt to advance the concept of embeddedness beyond the level of a programmatic statement by developing a formulation that specifies how embeddedness and network structure affect economic action. On the basis of existing theory and original ethnographies of 23 apparel firms, I develop a systematic scheme that more fully demarcates the unique features, functions, and sources of embeddedness. From this scheme, I derive a set of refutable implications and test their plausibility, using another data set on the network ties of all better dress apparel firms in the New York apparel economy. Results reveal that embeddedness is an exchange system with unique opportunities relative to markets and that firms organized in networks have higher survival chances than do firms which maintain arm's-length market relationships. The positive effect of embeddedness reaches a threshold, however, after which point the positive effect reverses itself.
Group emotional contagion, the transfer of moods among people in a group, and its influence on work group dynamics was examined in a laboratory study of managerial decision making using multiple, convergent measures of mood, individual attitudes, behavior, and group-level dynamics. Using a 2 times 2 experimental design, with a trained confederate enacting mood conditions, the predicted effect of emotional contagion was found among group members, using both outside coders' ratings of participants' mood and participants' self-reported mood. No hypothesized differences in contagion effects due to the degree of pleasantness of the mood expressed and the energy level with which it was conveyed were found. There was a significant influence of emotional contagion on individual-level attitudes and group processes. As predicted, the positive emotional contagion group members experienced improved cooperation, decreased conflict, and increased perceived task performance. Theoretical implications and practical ramifications of emotional contagion in groups and organizations are discussed.
This study focuses on the antecedents and consequences of displayed emotion in organizations. I propose that customers "catch" the affect of employees through emotional contagion processes. Results indicate that the display of positive emotion by employees is positively related to customers' positive affect following service encounters and to their evaluations of service quality. In a replication and extension of prior research, transaction busyness and employee emotional expressiveness are shown to predict displays of emotion by employees.
This study examines whether structural properties of friendship net-works condition the association between friends' delinquency and an individual's own delinquent behavior. Data from the Add Health allows a more accurate conceptualization of the peer network and a more rigorous measurement of peer delinquency than previous research. Findings from this study indicate that friends' delinquency is associated with an adolescent's own delinquency involvement. However, characteristics of adolescents' friendship networks, such as its density and adolescents' centrality and popularity, condition the delinquency-peer association. Network density, in particular, emerges as an important component of the delinquency-peer asso-ciation, with very cohesive networks containing stronger delin-quency-peer associations than those that are less cohesive. These findings suggest that it is necessary to consider the underlying struc-tural properties of friendship networks in order to understand the impact of peer influence on adolescent delinquency.
Recent analyses of social networks, both empirical and theoretical, are discussed, with a focus on how social networks influence economic behavior, as well as how social networks form. Some challenges of such research are discussed as are some of the important considerations for the future.
In a series of studies, we examine the role of positive emotions in the charismatic leadership process. In Studies 1 and 2, ratings of charisma in a natural work setting were linked to leaders' positive emotional expressions. In Study 3, leaders' positive emotional expressions were linked to mood states of simulated followers. Results suggest that mood contagion may be one of the psychological mechanisms by which charismatic leaders influence followers. In Study 4, we used a trained actor and manipulated leaders' positive emotional expressions to isolate the effects of positive emotions from the potential effects of non-emotional aspects of effective leadership (e.g., vision, other inspirational influence processes). A positive link between leader emotions and follower mood was found. Results also indicate that both leaders' positive emotional expressions and follower mood influenced ratings of leader effectiveness and attraction to the leader.
MUCH attention has been given to the Prisoners' Dilemma as a metaphor
for the problems surrounding the evolution of coopera-tive
behaviour1-6. This work has dealt with the relative merits of
various strategies (such as tit-for-tat) when players who recognize each
other meet repeatedly, and more recently with ensembles of strategies
and with the effects of occasional errors. Here we neglect all
strategical niceties or memories of past encounters, considering only
two simple kinds of players: those who always cooperate and those who
always defect. We explore the consequences of placing these players in a
two-dimensional spatial array: in each round, every individual 'plays
the game' with the immediate neighbours; after this, each site is
occupied either by its original owner or by one of the neighbours,
depending on who scores the highest total in that round; and so to the
next round of the game. This simple, and purely deterministic, spatial
version of the Prisoners' Dilemma, with no memories among players and no
strategical elaboration, can generate chaotically changing spatial
patterns, in which cooperators and defectors both persist indefinitely
(in fluctuating proportions about predictable long-term averages). If
the starting configurations are sufficiently symmetrical, these
ever-changing sequences of spatial patterns-dynamic fractals-can be
extraordinarily beautiful, and have interesting mathematical properties.
There are potential implications for the dynamics of a wide variety of
spatially extended systems in physics and biology.
Evidence shows that real-effort investments can affect bilateral bargaining outcomes. This paper investigates whether similar investments can inhibit equilibrium convergence of experimental markets. In one treatment, sellers’ relative effort affects the allocation of production costs, but a random productivity shock ensures that the allocation is not necessarily equitable. In another treatment, sellers’ effort increases the buyers’ valuation of a good. We find that effort investments have a short-lived impact on trading behavior when sellers’ effort benefits buyers, but no effect when effort determines cost allocation. Efficiency rates are high and do not differ across treatments.
A huge research literature, across the behavioral and social sciences, uses information on individuals’ subjective well-being.
These are responses to questions—asked by survey interviewers or medical personnel—such as, “How happy do you feel on a scale
from 1 to 4?” Yet there is little scientific evidence that such data are meaningful. This study examines a 2005–2008 Behavioral
Risk Factor Surveillance System random sample of 1.3 million U.S. citizens. Life satisfaction in each U.S. state is measured.
Across America, people’s answers trace out the same pattern of quality of life as previously estimated, from solely nonsubjective
data, in one branch of economics (so-called “compensating differentials” neoclassical theory, originally from Adam Smith).
There is a state-by-state match (r = 0.6, P < 0.001) between subjective and objective well-being. This result has some potential to help to unify disciplines.
Evolutionary dynamics are strongly affected by population structure. The outcome of an evolutionary process in a well-mixed population can be very different from that in a structured population. We introduce a powerful method to study dynamical population structure: evolutionary set theory. The individuals of a population are distributed over sets. Individuals interact with others who are in the same set. Any 2 individuals can have several sets in common. Some sets can be empty, whereas others have many members. Interactions occur in terms of an evolutionary game. The payoff of the game is interpreted as fitness. Both the strategy and the set memberships change under evolutionary updating. Therefore, the population structure itself is a consequence of evolutionary dynamics. We construct a general mathematical approach for studying any evolutionary game in set structured populations. As a particular example, we study the evolution of cooperation and derive precise conditions for cooperators to be selected over defectors.
The high variance of crime rates across time and space is one of the oldest puzzles in the social sciences; this variance
appears too high to be explained by changes in the exogenous costs and benefits of crime. We present a model where social
interactions create enough covariance across individuals to explain the high cross-city variance of crime rates. This model
provides an index of social interactions which suggests that the amount of social interactions is highest in petty crimes,
moderate in more serious crimes, and almost negligible in murder and rape.
To evaluate whether happiness can spread from person to person and whether niches of happiness form within social networks.
Longitudinal social network analysis.
Framingham Heart Study social network.
4739 individuals followed from 1983 to 2003.
Happiness measured with validated four item scale; broad array of attributes of social networks and diverse social ties.
Clusters of happy and unhappy people are visible in the network, and the relationship between people's happiness extends up to three degrees of separation (for example, to the friends of one's friends' friends). People who are surrounded by many happy people and those who are central in the network are more likely to become happy in the future. Longitudinal statistical models suggest that clusters of happiness result from the spread of happiness and not just a tendency for people to associate with similar individuals. A friend who lives within a mile (about 1.6 km) and who becomes happy increases the probability that a person is happy by 25% (95% confidence interval 1% to 57%). Similar effects are seen in coresident spouses (8%, 0.2% to 16%), siblings who live within a mile (14%, 1% to 28%), and next door neighbours (34%, 7% to 70%). Effects are not seen between coworkers. The effect decays with time and with geographical separation.
People's happiness depends on the happiness of others with whom they are connected. This provides further justification for seeing happiness, like health, as a collective phenomenon.
Predicting the likely success of invasions is vitally important in ecology and especially epidemiology. Whether an organism can successfully invade and persist in the short-term is highly dependent on the spatial correlations that develop in the early stages of invasion. By modelling the correlations between individuals, we are able to understand the role of spatial heterogeneity in invasion dynamics without the need for large-scale computer simulations. Here, a natural methodology is developed for modelling the behaviour of individuals in a fixed network. This formulation is applied to the spread of a disease through a structured network to determine invasion thresholds and some statistical properties of a single epidemic.
To determine whether positive affect has an independent effect on functional status, mobility, and survival in an older Mexican American sample.
A 2-year prospective cohort study.
Five Southwestern states: Texas, California, Arizona, New Mexico, and Colorado.
A population-based sample of 2282 Mexican Americans aged 65 to 99 who reported no functional limitations at baseline interview.
In-home interviews in 1993-1994 and again in 1995-1996 assessed demographic variables, health conditions, activities of daily living, performance-based mobility, survival, and a rating of positive and negative affect.
In multivariate analyses, there was a direct relationship between positive affect scores at baseline and mobility, functional status, and survival 2 years later, controlling for functional status, sociodemographic variables, major chronic conditions, body mass index (BMI), smoking status, drinking status, and negative affect at baseline. Subjects with high positive affect were half as likely (odds ratio (OR) = 0.48; 95% confidence interval (CI) 0.29, 0.93) to become disabled in activities of daily living (ADLs), two-thirds as likely (OR = 0.64; 95% CI 0.51, 0.79) to have a slow walking speed, and half as likely (OR 0.53; 95% CI 0.30, 0.93) to have died during the 2-year follow-up compared to those with lower positive affect scores.
Our results support the concept that positive affect, or emotional well-being, is different from the absence of depression or negative affect. Positive affect seems to protect individuals against physical declines in old age.
The Internet has a very complex connectivity recently modeled by the class of scale-free networks. This feature, which appears to be very efficient for a communications network, favors at the same time the spreading of computer viruses. We analyze real data from computer virus infections and find the average lifetime and persistence of viral strains on the Internet. We define a dynamical model for the spreading of infections on scale-free networks, finding the absence of an epidemic threshold and its associated critical behavior. This new epidemiological framework rationalizes data of computer viruses and could help in the understanding of other spreading phenomena on communication and social networks.
We present an analysis of the current foot-and-mouth disease epidemic in Great Britain over the first 2 months of the spread
of the virus. The net transmission potential of the pathogen and the increasing impact of control measures are estimated over
the course of the epidemic to date. These results are used to parameterize a mathematical model of disease transmission that
captures the differing spatial contact patterns between farms before and after the imposition of movement restrictions. The
model is used to make predictions of future incidence and to simulate the impact of additional control strategies. Hastening
the slaughter of animals with suspected infection is predicted to slow the epidemic, but more drastic action, such as “ring”
culling or vaccination around infection foci, is necessary for more rapid control. Culling is predicted to be more effective
than vaccination.
A wide range of communicable human diseases can be considered as spreading through a network of possible transmission routes. The implied network structure is vital in determining disease dynamics, especially when the average number of connections per individual is small as is the case for many sexually transmitted diseases (STDs). Here we develop an intuitive mathematical framework to deal with the heterogeneities implicit within contact networks and those that arise because of the infection process. These models are compared with full stochastic simulations and show excellent agreement across a wide range of parameters. We show how such models can be used to estimate parameters of epidemiological importance, and how they can be extended to examine the effectiveness of various control strategies, in particular screening programs and contact tracing.
It is not known whether the risk of recurrence declines with time in bipolar disorders and in major depression. This study describes the life-long recurrence risk of bipolar I, bipolar II and major depressive disorders.
160 bipolar-I, 60 bipolar-II and 186 depressive patients hospitalised between 1959 and 1963 were followed up every five years from 1965 to 1985. The course prior to the index hospitalisation was assessed in retrospect. The recurrence risk was computed by the multiplicative intensity model (Aalen et al. 1980).
The cumulative intensity curves for the transition from states of remission to new episodes remained linear over 30 to 40 years after onset, indicating a constant risk of recurrence over the life-span up to the age of 70 or more. The recurrence risk of bipolar disorders (0.40 episodes per year) was about twice that of depression (0.20 episodes per year); BP-II disorders had only a slightly higher recurrence risk than BP-I disorders. There were no significant gender differences in the course of either bipolar or depressive disorders.
If long-term trials confirm its efficacy, these results support lifelong prophylactic treatment of severe types of mood disorders.
We investigated the relationship between friendships and suicidality among male and female adolescents.
We analyzed friendship data on 13,465 adolescents from the National Longitudinal Survey of Adolescent Health to explore the relationship between friendship and suicidal ideation and suicide attempts. We controlled for known factors associated with suicidality.
Having had a friend who committed suicide increased the likelihood of suicidal ideation and attempts for both boys and girls. Socially isolated females were more likely to have suicidal thoughts, as were females whose friends were not friends with each other. Among adolescents thinking about suicide, suicide attempts appear largely stochastic, with few consistent risk factors between boys and girls.
The friendship environment affects suicidality for both boys and girls. Female adolescents' suicidal thoughts are significantly increased by social isolation and friendship patterns in which friends were not friends with each other.
This review highlights consistent patterns in the literature associating positive affect (PA) and physical health. However, it also raises serious conceptual and methodological reservations. Evidence suggests an association of trait PA and lower morbidity and of state and trait PA and decreased symptoms and pain. Trait PA is also associated with increased longevity among older community-dwelling individuals. The literature on PA and surviving serious illness is inconsistent. Experimentally inducing intense bouts of activated state PA triggers short-term rises in physiological arousal and associated (potentially harmful) effects on immune, cardiovascular, and pulmonary function. However, arousing effects of state PA are not generally found in naturalistic ambulatory studies in which bouts of PA are typically less intense and often associated with health protective responses. A theoretical framework to guide further study is proposed.
A fundamental aspect of all biological systems is cooperation. Cooperative interactions are required for many levels of biological organization ranging from single cells to groups of animals. Human society is based to a large extent on mechanisms that promote cooperation. It is well known that in unstructured populations, natural selection favours defectors over cooperators. There is much current interest, however, in studying evolutionary games in structured populations and on graphs. These efforts recognize the fact that who-meets-whom is not random, but determined by spatial relationships or social networks. Here we describe a surprisingly simple rule that is a good approximation for all graphs that we have analysed, including cycles, spatial lattices, random regular graphs, random graphs and scale-free networks: natural selection favours cooperation, if the benefit of the altruistic act, b, divided by the cost, c, exceeds the average number of neighbours, k, which means b/c > k. In this case, cooperation can evolve as a consequence of 'social viscosity' even in the absence of reputation effects or strategic complexity.
Networks and the epidemiology of directly transmitted infectious diseases are fundamentally linked. The foundations of epidemiology and early epidemiological models were based on population wide random-mixing, but in practice each individual has a finite set of contacts to whom they can pass infection; the ensemble of all such contacts forms a ‘mixing network’. Knowledge of the structure of the network allows models to compute the epidemic dynamics at the population scale from the individual-level behaviour of infections. Therefore, characteristics of mixing networks—and how these deviate from the random-mixing norm—have become important applied concerns that may enhance the understanding and prediction of epidemic patterns and intervention measures.
Here, we review the basis of epidemiological theory (based on random-mixing models) and network theory (based on work from the social sciences and graph theory). We then describe a variety of methods that allow the mixing network, or an approximation to the network, to be ascertained. It is often the case that time and resources limit our ability to accurately find all connections within a network, and hence a generic understanding of the relationship between network structure and disease dynamics is needed. Therefore, we review some of the variety of idealized network types and approximation techniques that have been utilized to elucidate this link. Finally, we look to the future to suggest how the two fields of network theory and epidemiological modelling can deliver an improved understanding of disease dynamics and better public health through effective disease control.
A meta-analysis of 40 findings from 36 studies (N = 4,952) provided substantial overall support for the proposition that depressive symptoms and mood are contagious. Contagion appeared most pronounced in studies of depressive symptoms (vs. depressive mood). Contagion of depressive mood appears to depend on methodological approach, with strongest to weakest results in the following order: transcript studies, audio/ videotape studies, studies using actual strangers, studies using actual friends/acquaintances, and confederate studies. Contagion of depressed mood/symptoms held across combinations of target x respondent gender. There was very tentative evidence that contagion was specific to depressive versus other symptom/moods. Based in part on our meta-analytic findings, we summarize possible explanations of the phenomenon from cognitive, behavioral, and interpersonal viewpoints and elucidate some clinical implications.
The prevalence of obesity has increased substantially over the past 30 years. We performed a quantitative analysis of the nature and extent of the person-to-person spread of obesity as a possible factor contributing to the obesity epidemic.
We evaluated a densely interconnected social network of 12,067 people assessed repeatedly from 1971 to 2003 as part of the Framingham Heart Study. The body-mass index was available for all subjects. We used longitudinal statistical models to examine whether weight gain in one person was associated with weight gain in his or her friends, siblings, spouse, and neighbors.
Discernible clusters of obese persons (body-mass index [the weight in kilograms divided by the square of the height in meters], > or =30) were present in the network at all time points, and the clusters extended to three degrees of separation. These clusters did not appear to be solely attributable to the selective formation of social ties among obese persons. A person's chances of becoming obese increased by 57% (95% confidence interval [CI], 6 to 123) if he or she had a friend who became obese in a given interval. Among pairs of adult siblings, if one sibling became obese, the chance that the other would become obese increased by 40% (95% CI, 21 to 60). If one spouse became obese, the likelihood that the other spouse would become obese increased by 37% (95% CI, 7 to 73). These effects were not seen among neighbors in the immediate geographic location. Persons of the same sex had relatively greater influence on each other than those of the opposite sex. The spread of smoking cessation did not account for the spread of obesity in the network.
Network phenomena appear to be relevant to the biologic and behavioral trait of obesity, and obesity appears to spread through social ties. These findings have implications for clinical and public health interventions.
This collection of articles brings together studies that examine the transmission of emotions between family members. All studies employ repeated diary or experience-sampling data to examine daily within-person and within-family variations in emotional experience. Emotional transmission is evaluated by assessing circumstances in which events or emotions in one family member's immediate experience show a consistent, predictive relationship to subsequent emotions or behaviors in another family member. This introduction places this empirical paradigm in the context of other approaches to research, discusses research methods and statistical procedures for studying emotional transmission, and reviews the major findings obtained thus far in this body of research. We argue that this empirical paradigm provides a promising tool for understanding emotional processes within the daily ecology of family and community life.
The CES-D scale is a short self-report scale designed to measure depressive symptomatology in the general population. The items of the scale are symptoms associated with depression which have been used in previously validated longer scales. The new scale was tested in household interview surveys and in psychiatric settings. It was found to have very high internal consistency and adequate test- retest repeatability. Validity was established by pat terns of correlations with other self-report measures, by correlations with clinical ratings of depression, and by relationships with other variables which support its construct validity. Reliability, validity, and factor structure were similar across a wide variety of demographic characteristics in the general population samples tested. The scale should be a useful tool for epidemiologic studies of de pression.
A study of "the dynamics of person-to-person communication and influence" as compared to the apparent direct effect of mass media. The authors have found evidence of the "possible relevance of interpersonal relations as an intervening variable in the mass communications process." The latter half of the book is concerned with a research carried on in Decatur, Illinois, upon a cross-section sample of 800 women in which a variety of reaction producing influences were studied to determine the degree and extent of their impact on ultimate behavior. Factors influencing leadership status were analyzed. 180-item bibliography. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
A meta-analysis of 40 findings from 36 studies (N= 4,952) provided substantial overall support for the proposition that depressive symptoms and mood are contagious. Contagion appeared most pronounced in studies of depressive symptoms (vs. depressive mood). Contagion of depressive mood appears to depend on methodological approach, with strongest to weakest results in the following order: transcript studies, audio/ videotape studies, studies using actual strangers, studies using actual friends/acquaintances, and confederate studies. Contagion of depressed mood/symptoms held across combinations of target × respondent gender. There was very tentative evidence that contagion was specific to depressive versus other symptom/moods. Based in part on our meta-analytic findings, we summarize possible explanations of the phenomenon from cognitive, behavioral, and interpersonal viewpoints and elucidate some clinical implications.
People are interconnected, and so their health is interconnected. In recognition of this social fact, there has been growing conceptual and empirical attention over the past decade to the impact of social networks on health. This article reviews prominent findings from this literature. After drawing a distinction between social network studies and social support studies, we explore current research on dyadic and supradyadic network influences on health, highlighting findings from both egocen-tric and sociocentric analyses. We then discuss the policy implications of this body of work, as well as future research directions. We conclude that the existence of social networks means that people's health is inter-dependent and that health and health care can transcend the individual in ways that patients, doctors, policy makers, and researchers should care about.
Previous studies have demonstrated that individuals who are socially integrated have better mental health, but these studies have been mostly limited to the adult population. Using data based on a nationally representative sample of adolescents (N = 11,023), I investigate whether those who are integrated into friendship networks have better mental health, as measured by number of depressive symptoms. The study also extends the literature by utilizing a variety of network measures of integration. The analyses showed that, consistent with previous findings in the adult studies, higher levels of integration were associated with fewer depressive symptoms, although the association was very weak. Number of friends, the simplest and most frequently used measure of integration in mental health research, had a stronger and more consistent effect than other variables which measured more complex aspects of egocentric and school-level network structure. The results also showed that the relationship between having more friends and fewer depressive symptoms was largely mediated by a sense of belonging, which provided support for the often assumed but rarely tested argument that social integration promotes mental health by inducing positive feelings about one’s relationships with others in society.
We investigate two paradigms for studying the evolution of cooperation—Prisoner's Dilemma and Snowdrift game in an online friendship network, obtained from a social networking site. By structural analysis, it is revealed that the empirical social network has small-world and scale-free properties. Besides, it exhibits assortative mixing pattern. Then, we study the evolutionary version of the two types of games on it. It is found that cooperation is substantially promoted with small values of game matrix parameters in both games. Whereas the competent cooperators induced by the underlying network of contacts will be dramatically inhibited with increasing values of the game parameters. Further, we explore the role of assortativity in evolution of cooperation by random edge rewiring. We find that increasing amount of assortativity will to a certain extent diminish the cooperation level. We also show that connected large hubs are capable of maintaining cooperation. The evolution of cooperation on empirical networks is influenced by various network effects in a combined manner, compared with that on model networks. Our results can help understand the cooperative behaviors in human groups and society.
We examine how Dartmouth College seniors use social networks to obtain their first jobs. We do this by analyzing self reports of networking and by examining the correlation in employment outcomes among randomly assigned freshman roommates and hallmates. We find that the use of social networks differs for men and women and for white and nonwhite students. Networking also differs greatly across career types. Students networking with fraternity and sorority members and alumni are the most likely to obtain high paying jobs. There is a strong connection between own employment outcomes and outcomes for randomly assigned freshmen hallmates.
Evolutionary game theory studies frequency dependent selection. The fitness of a strategy is not constant, but depends on the relative frequencies of strategies in the population. This type of evolutionary dynamics occurs in many settings of ecology, infectious disease dynamics, animal behavior and social interactions of humans. Traditionally evolutionary game dynamics are studied in well-mixed populations, where the interaction between any two individuals is equally likely. There have also been several approaches to study evolutionary games in structured populations. In this paper we present a simple result that holds for a large variety of population structures. We consider the game between two strategies, A and B, described by the payoff matrix . We study a mutation and selection process. For weak selection strategy A is favored over B if and only if σa+b>c+σd. This means the effect of population structure on strategy selection can be described by a single parameter, σ. We present the values of σ for various examples including the well-mixed population, games on graphs, games in phenotype space and games on sets. We give a proof for the existence of such a σ, which holds for all population structures and update rules that have certain (natural) properties. We assume weak selection, but allow any mutation rate. We discuss the relationship between σ and the critical benefit to cost ratio for the evolution of cooperation. The single parameter, σ, allows us to quantify the ability of a population structure to promote the evolution of cooperation or to choose efficient equilibria in coordination games.
Incluye bibliografía e índice
Theoretical models suggest that social networks influence the evolution of cooperation, but to date there have been few experimental studies. Observational data suggest that a wide variety of behaviors may spread in human social networks, but subjects in such studies can choose to befriend people with similar behaviors, posing difficulty for causal inference. Here, we exploit a seminal set of laboratory experiments that originally showed that voluntary costly punishment can help sustain cooperation. In these experiments, subjects were randomly assigned to a sequence of different groups to play a series of single-shot public goods games with strangers; this feature allowed us to draw networks of interactions to explore how cooperative and uncooperative behaviors spread from person to person to person. We show that, in both an ordinary public goods game and in a public goods game with punishment, focal individuals are influenced by fellow group members' contribution behavior in future interactions with other individuals who were not a party to the initial interaction. Furthermore, this influence persists for multiple periods and spreads up to three degrees of separation (from person to person to person to person). The results suggest that each additional contribution a subject makes to the public good in the first period is tripled over the course of the experiment by other subjects who are directly or indirectly influenced to contribute more as a consequence. These results show experimentally that cooperative behavior cascades in human social networks.
This paper uses a unique data set to measure peer effects among college roommates. Freshman year roommates and dormmates are randomly assigned at Dartmouth College. I find that peers have an impact on grade point average and on decisions to join social groups such as fraternities. Residential peer effects are markedly absent in other major life decisions such as choice of college major. Peer effects in GPA occur at the individual room level, whereas peer effects in fraternity membership occur both at the room level and the entire dorm level. Overall, the data provide strong evidence for the existence of peer effects in student outcomes. © 2001 the President and Fellows of Harvard College and the Massachusetts Institute of Technology
This paper uses social networks to identify information transfer in security markets. We focus on connections between mutual fund managers and corporate board members via shared education networks. We find that portfolio managers place larger bets on connected firms and perform significantly better on these holdings relative to their nonconnected holdings. A replicating portfolio of connected stocks outperforms nonconnected stocks by up to 7.8 percent per year. Returns are concentrated around corporate news announcements, consistent with portfolio managers gaining an informational advantage through the education networks. Our results suggest that social networks may be important mechanisms for information flow into asset prices. (c) 2008 by The University of Chicago. All rights reserved..
Review of the published literature produces 1-year prevalence rates for major depressive disorder DSM-III between 2.6 and 6.2%, for dysthymia between 2.3 and 3.7%, bipolar disorder 1.0-1.7%. Data from the prospective Zurich Study with four interviews over 10 years give relatively high 10-year prevalence rates for subjects from age 20 to 30 (14.4% major depression, 10.5% recurrent brief depression, 0.9% dysthymia, 3.3% bipolar disorder, 1.3% hypomania). On average, 49% of all these cases received treatment for affective disorder, resulting in a weighted treatment prevalence rate of the population of 11.6% (18% for females and 5% for males). It has to be assumed that lifetime prevalence rates based on recall may greatly underestimate true morbidity.
Scores on the Beck Depression Inventory (BDI) were periodically obtained from the roommates of college students who exhibited a persistent mild depression over a 3-month period. For comparative purposes, BDI scores were also obtained from roommates of individuals who were transiently depressed and from subjects with nondepressed roommates. In comparison with control subjects, the roommates of persistently depressed persons displayed a progressive increase in BDI score over the course of the study.
Reliability of the Center for Epidemiologic Studies Depression Scale, a 20-item symptom checklist, is examined using data from a sample of community respondents containing Anglos (254), Blacks (270), and Mexican Americans (181). Although the survey response rate was lower for Mexican Americans, quality of the data provided by this group was not significantly different from that for Anglos or Blacks. That is, there were no differences among these groups in terms of missing data or internal consistency reliabilty (as measured by Cronbach's alpha and Spearman-Brown split halves). Factor-analytic results also demonstrate the same general structure of responses among the three groups.
