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Is Dunbar's Number Up?

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This article is a commentary on 'Relationships and the social brain: Integrating psychological and evolutionary perspectives' (Sutcliffe, Dunbar, Binder, & Arrow, 2012).

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... He found a correlation between the size of an average human brain's neocortex and social group sizes, and defined that the cognitive constraint to the number of individuals humans can maintain social relationships with is around 150. However, Wellman [3] claims that OSNs disrupted the theory behind the Dunbar's Number and that people in the OSN era have more close ties than people in past generations. Therefore, the second contribution of this paper is the confirmation of Wellman's theory that people who regularly use Facebook changed the limits defined by the Dunbar's Number. ...
... Therefore, it is unlikely that the cognitive capacities of modern humans are limited to 150 meaningful relationships, as stated by Dunbar. Furthermore, Wellman [3] argues that the Dunbar's number is up through disagreeing with the Dunbar's claim that relationships are structured as a series of concentric circles of support, sympathy, affinity and activity that scale relative to each other by a factor of 3. He argues that relationships are not tiered because in reality relationships among individuals are more complicated than a situation that the closest layer only provides support while the next closest layer only provides sympathy. ...
... When comparing these values with the Dunbar's social circles [2], [13]- [15], it is clear that people today have more individuals in social circles because of worldwide penetration of Internet and OSNs, as well as the availability of smartphones. Therefore, we confirmed Wellman's theory [3] Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. ...
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This paper presents the “SmartSocial Dataset” which describes 1,826 Facebook users with lots of details, including their connections and their interactions (e.g., posts, likes, comments). We firstly present a detailed analysis of (i) descriptive and (ii) network characteristics of the “SmartSocial Dataset” to provide evidence for its representativeness. Afterwards, we analyse the relationship between social and behavioural characteristics of “SmartSocial Dataset” users and Benford’s Law as well as Dunbar’s Number, to test whether Facebook has the power to change natural (Benford) and anthropological (Dunbar) laws. We find that Fakebook’s features are aligned with the Benford’s Law but redefine the way how Dunbar’s Number is calculated. Finally, we demonstrate how those findings could help researchers and business practitioners who collect Facebook datasets in a way to indicate whether there is serious sampling problem with the dataset they collected.
... Thus, to date, social signature theory has limited empirical support. Furthermore, alternative theories claim that modern communication devices and services, such as online social networks (OSNs) may allow humans to break through their cognitive limits and reach the numbers of alters far greater than 150 or 250 (Wellman, 2011). ...
... Alternative theories claim that social networking sites are able to help individuals cut through the limit of the Dunbar's number (Wellman, 2011). Thus, different studies find that heavy internet users tend to have larger offline and online networks than light users and gain more ties with time (Wang & Wellman, 2010); larger online ego-networks contribute to the increase of strong ties, albeit not as much as to the growth of weak ties (Manago et al., 2012), larger online ego-networks are associated with larger core discussion networks (Vriens & van Ingen, 2018), and certain types of heavy internet use contribute to higher numbers of social ties (Zhao, 2006). ...
... Additionally, it has been shown that larger online personal networks are associated with higher perceived social capitalthat is, the perceived amount of resources that alters can share with an ego, or the perceived amount of help an ego can get from them (Ellison et al., 2014). Wellman (Rainie & Wellman, 2012;Wellman, 2011) also reviews the works (e.g. Bernard et al., 2001;McCormick et al., 2010) that estimate human networks to be much larger than 150, amounting to 1000 and more, depending on how connections are understood. ...
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Social tie maintenance has always had cognitive and emotional costs and has been leading to uneven distribution of communication volume among interaction partners of individuals. This distribution, known as social signature, is assumed to be stable for each person. Availability of digital traces of human communication allows testing whether this assumption is true and whether it holds in specific channels of computer-mediated communication. In this paper, we investigate private messaging on a popular social networking website on a sample of 39 users and 8063 communication partners of those users over the period of 18 months. We find that this communication channel does not reduce cognitive costs as the overall number of users’ active contacts, on average, is equivalent to the cognitive limit known as Dunbar’s number. Confirming some previous research, we show that the volume of communication is unevenly distributed, related to emotional closeness, and that changes in this distribution (that is, the changes in social signature) over time within an individual are smaller than the distances between social signatures of different individuals. However, as an absolutely novel finding, we demonstrate that the changes within individuals are statistically significant, thus questioning the concept of social signature as a stable phenomenon.
... Unfortunately, this claim ignores the fact that these band groupings are unstable and purely ecological in origin-and are clearly embedded in a stable larger community such that band members are drawn only from this community (occasional visitors excepted) [2,[36][37][38]. The other has been to claim that the natural size of human communities must be much greater because we know many more than 150 individuals or because we can list many more individuals as Facebook friends [39]. In the latter case, the issue involves confusion between real social relationships and the capacity to remember faces/ names. ...
... So how is it that many claim that digital media do yield larger social networks [39,82]? It seems likely that there are two quite separate issues here. ...
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The social brain hypothesis (an explanation for the evolution of brain size in primates) predicts that humans typically cannot maintain more than 150 relationships at any one time. The constraint is partly cognitive (ultimately determined by some aspect of brain volume) and partly one of time. Friendships (but not necessarily kin relationships) are maintained by investing time in them, and failure to do so results in an inexorable deterioration in the quality of a relationship. The Internet, and in particular the rise of social networking sites (SNSs), raises the possibility that digital media might allow us to circumvent some or all of these constraints. This allows us to test the importance of these constraints in limiting human sociality. Although the recency of SNSs means that there have been relatively few studies, those that are available suggest that, in general, the ability to broadcast to many individuals at once, and the possibilities this provides in terms of continuously updating our understanding of network members' behaviour and thoughts, do not allow larger networks to be maintained. This may be because only relatively weak quality relationships can be maintained without face-to-face interaction.
... With the advent of different types of super social networking services developing one after another, people have once again picked up the topic for discussion [43], [44]. Many researchers have investigated how tools, such as Facebook and Twitter, have changed our capacity to handle social connections using the empirical study [45]- [47]. Here, Fig. 5(a) and (b) also shows the shadow of Dunbar's number on Sina-Weibo. ...
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Social media analytics has drawn new quantitative insights of human activity patterns. Many applications of social media analytics, from pandemic prediction to earthquake response, require an in-depth understanding of how these patterns change when human encounter unfamiliar conditions. In this paper, we select two earthquakes in China as the social context in Sina-Weibo (or Weibo for short), the largest Chinese microblog site. After proposing a formalized Weibo information flow model to represent the information spread on Weibo, we study the information spread from three main perspectives: individual characteristics, the types of social relationships between interactive participants, and the topology of real interaction networks. The quantitative analyses draw the following conclusions. First, the shadow of Dunbar's number is evident in the "declared friends/followers" distributions, and the number of each participant's friends/followers who also participated in the earthquake information dissemination show the typical power-law distribution, indicating a rich-gets-richer phenomenon. Second, an individual's number of followers is the most critical factor in user influence. Strangers are very important forces for disseminating real-time news after an earthquake. Third, two types of real interaction networks share the scale-free and small-world property, but with a looser organizational structure. In addition, correlations between different influence groups indicate that when compared with other online social media, the discussion on Weibo is mainly dominated and influenced by verified users.
... A number of commentators have voiced opinions consistent with this idea. Wellman [540], for example, suggests that "social media have increased the carrying capacity of relationships, with heavy internet users having more close ties" (p. 174). ...
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Alongside existing research into the social, political and economic impacts of the Web, there is a need to study the Web from a cognitive and epistemic perspective. This is particularly so as new and emerging technologies alter the nature of our interactive engagements with the Web, transforming the extent to which our thoughts and actions are shaped by the online environment. Situated and ecological approaches to cognition are relevant to understanding the cognitive significance of the Web because of the emphasis they place on forces and factors that reside at the level of agent-world interactions. In particular, by adopting a situated or ecological approach to cognition, we are able to assess the significance of the Web from the perspective of research into embodied, extended, embedded, social and collective cognition. The results of this analysis help to reshape the interdisciplinary configuration of Web Science, expanding its theoretical and empirical remit to include the disciplines of both cognitive science and the philosophy of mind. Minds Online: The Interface between Web Science, Cognitive Science and the Philosophy of Mind heeds the call of the early Web Science pioneers by expanding the interdisciplinary scope of Web Science, specifically, to accommodate the disciplines of cognitive science and the philosophy of mind. There is a substantial literature to support this expansionist agenda. Given the centrality of cognition to our species-specific capabilities, as well as the level of public and scientific interest in the Web, now is arguably an appropriate time to review this literature and explicate the nature of the linkages that connect the science of the Web with the sciences of the mind.
... For example, the famous Dunbar's number, which estimates the number of active relationships, is 150 [4]. More recent studies seem to indicate that the average number of acquaintances is larger, ranging from 250 to 1500 (see [3,16,22] and references within). We propose to set p and q so that the neighborhood size 2p(p + 1) + q is about 600, the value reported in [16]. ...
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One of the key features of small-worlds is the ability to route messages with few hops only using local knowledge of the topology. In 2000, Kleinberg proposed a model based on an augmented grid that asymptotically exhibits such property. In this paper, we propose to revisit the original model from a simulation-based perspective. Our approach is fueled by a new algorithm that uses dynamic rejection sampling to draw augmenting links. The speed gain offered by the algorithm enables a detailed numerical evaluation. We show for example that in practice, the augmented scheme proposed by Kleinberg is more robust than predicted by the asymptotic behavior, even for very large finite grids. We also propose tighter bounds on the performance of Kleinberg's routing algorithm. At last, we show that fed with realistic parameters, the model gives results in line with real-life experiments.
... A number of commentators have voiced opinions consistent with this idea. Wellman [540], for example, suggests that "social media have increased the carrying capacity of relationships, with heavy internet users having more close ties" (p. 174). ...
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... These studies led to vastly different estimates of average network size (see Table 1): from less than 100 (free recall; contact diaries for a limited period; online social networks) up to thousands (extrapolation from telephone book experiments or from prolonged contact diaries, participant observation), depending among others on the method of estimation, the characteristics of the sample, and the underlying definition of "knowing someone" (the network boundary). However, many studies found much higher averages than 150, concluding that Dunbar's number is on the low side for modern societies (e.g., Wellman, 2012). A mechanism that may explain the higher numbers given limited cognitive capacity is the use of compression heuristics among humans (Brashears, 2013), allowing the storage of larger amounts of information about social relationships in the brain. ...
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... For example, the famous Dunbar's number, which estimates the number of active relationships, is 150 [24]. More recent studies seem to indicate that the average number of acquaintances is larger, ranging from 250 to 1500 (see [25,26,27] and references within). We propose to set p and q so that the neighborhood size 2p(p + 1) + q is about 600, the value reported in [26]. ...
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... Consistent with Dunbar's number, social networks are constrained by the number of social relationships that can be functionally sustained, typically between 80 and 300 nodes (Arnaboldi et al., 2013;LaRose et al., 2014;Liang & Fu, 2015;Mac Carron et al., 2016;Miritello, Lara, et al., 2013a;Sandel et al., 2016;M. Stephens & Poorthuis, 2015;cf., Manago, Taylor, & Greenfield, 2012;Wellman, 2012). In addition to support from research on ordinary social networks (e.g., Dunbar & Sosis, 2018), various studies of mediated network topologies have tended to support these ranges of social ties (Arnaboldi et al., 2013). ...
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The study of personal relationships has traditionally relied on self‐reports or observations of face‐to‐face interaction. Digital media increasingly provide the ability to trace communication and relationships at scale. Such methods portend significant theoretical and methodological challenges, as well as potential. As a way of illustrating such potential, big data approaches to the select traditional relational concepts of routine relating, propinquity, homophily, small world, and reciprocity are reviewed. The fields of communication and personal relationships will need to inform such research by developing their own interdisciplinary relationships with geographic information sciences, computational linguistics, and computer sciences or cede a significant frontier of their field to these other disciplines.
... Dunbar's "cognitive limit" no longer holds in our modern interconnected world, where the nature of our personal networks has changed both quantitatively and qualitatively. Estimates now suggest that an individual can have a mean number of well over 600 connections (Wellman, 2012). Add to this, the multiplier effects that come with interconnectivity and the user interface of social media. ...
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... SD = 2,256.90). Although the cut-off values for the number of friends in small and medium social network groups are higher than those identified by Dunbar (2011) and Dunbar et al. (2015), researchers have recognized that there is wide variance around the mean network sizes (e.g., for the mean network size of 150, the lower and upper bounds are 100 and 250) (Dunbar, 2018) and are likely to be higher in an online context (Wellman, 2012). As such, the difference in values for social network sizes between our study and those identified by Dunbar (2011) and Dunbar et al. (2015) is unlikely to be of major concern. ...
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... distant) relationships are viewed with greater trust, stronger memories, and deeper support , contributing to the fundamental distinctions between "close" vs. "distal" others (Trope & Liberman, 2010) and "strong" vs. "weak" ties (Granovetter, 1973). While there are many dimensions that can contribute to the depth or value of a given relationship (Fingerman, 2009;Wellman, 2012), here we focus on perceived closeness, or the extent to which another individual is perceived as close (Triê _ u et al., 2019). From this lens, romantic partners and loyal friends are likely to be perceived as very close, whereas the barista at the local coffee stop is unlikely to be seen as close-unless one has established a rapport from regular visits. ...
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... All communication activities, including face-to-face interactions and social media use, are competing for the individual's attention (Zulli, 2018). Considering the time-intensive requirements for maintaining a friendship, it may be more time efficient for individuals to keep in touch via social media instead of other communication channels (e.g., face-to-face interactions, texting, phone calls; Wellman, 2012). Additionally, because Finsta is thought to present a more authentic and realistic version of users when compared to traditional Instagram, one does not have to invest as much energy into self-presentation in their Finsta interactions (Duffy & Chan, 2019). ...
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... The number of 'friends' a person has on Facebook, for example, is often significantly larger than the size of a person's real-world social network (Kanai et al., 2012). This difference in size is partially attributable to the greater ease with 55 which online vs real-world social connections can be initiated and maintained, but other factors such as differences in the purpose of maintaining online vs real-world social networks could also play a role (Lewis et al., 2008;Wellman, 2012). There are also inconsistencies between various measures of real-world SNS. ...
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... It has been suggested that, even if this limit on personal network size exists in the face-to-face world, the rise of online SNSs has circumvented at least some of these constraints and has thus allowed us to increase dramatically the number of people we can have as friends [9,[37][38][39]. Because there are significant limits on the number of people we can talk to at any one time in the offline world [40][41][42] as well as on the amount of time we have available for social interaction [25,43], there is inevitably a limit on the size of our egocentric social networks when relationships require time investment. ...
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Since about five years, the MIT Center for Collective Intelligence, Cambridge, U.S., and the Chronic Collaborative Care Network (C3N) at Cincinnati Children’s Hospital, Cincinnati, U.S., have been working together to improve care for inflammatory bowel disease (IBD) patients by harnessing methods of computational social science. The goal of this contribution is (1) to present an approach in measuring communication patterns and sentiments within online communities of IBD patients, (2) to analyze the enablers for a better connectedness of community members, and (3) to introduce a prototype application of a collective intelligent online network for IBD patients, named “YouMeIBD”. The mobile application, developed within an interdisciplinary student class at MIT and four other universities, aims to improve the connectedness, well-being and diffusion of innovations in a community of IBD patients.
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Anfang der 1990er Jahren stellt Dunbar, ein auf Primatenforschung spezialisierter britischer Anthropologe und Evolutionsbiologe, die später sogenannte » Soziale-Gehirn- Hypothese « (engl. social brain hypothesis) auf, welche die Anzahl der Freunde als eine Eigenschaft und Funktion des Neocortex beschreibt, da es sowohl kognitive als auch zeitliche Begrenzungen gebe, Freundschaften aufrecht zu erhalten. Hierfür zieht Dunbar Studien über die Gruppengröße von 36 verschiedenen Primaten heran und korreliert diese mit der Gehirngröße der entsprechenden Primaten, um daraus eine mathematische Formel zu generieren. Mit deren Hilfe bestimmt er die » durchschnittliche Gruppengröße « für Menschen mit 147,8, wobei meist die aufgerundete Zahl von 150 verwandt wird.
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Spatializing Social Media charts the theoretical and methodological challenges in analyzing and visualizing social media data mapped to geographic areas. It introduces the reader to concepts, theories, and methods that sit at the crossroads between spatial and social network analysis to unpack the conceptual differences between online and face-to-face social networks and the nonlinear effects triggered by social activity that overlaps online and offline. The book is divided into four sections, with the first accounting for the differences between space (the geometrical arrangements that structure and enable forms of interaction) and place (the mechanisms through which social meanings are attached to physical locations). The second section covers the rationale of social network analysis and the ontological differences, stating that relationships, more than individual and independent attributes, are key to understanding of social behavior. The third section covers a range of case studies that successfully mapped social media activity to geographically situated areas and considers the inflection of homophilous dependencies across online and offline social networks. The fourth and last section of the book explores a range of networks and discusses methods for and approaches to plotting a social network graph onto a map, including the purpose-built R package Spatial Social Media. The book takes a non-mathematical approach to social networks and spatial statistics suitable for postgraduate students in sociology, psychology and the social sciences.
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Originally conceived to highlight problematic labor relations that required emotions, the term emotional labor is now deployed to describe emotional relations that require problematic labor. In this paper, we identify how digital platforms have amplified this inverted form of emotional labor and spawned a phenomenon we term technoliberal managerialism, or the use of the connection, quantification, control, tracking, and optimization capacities of technology to manage everyday interactions. Through the analysis of viral self-help Twitter threads, a mobile application, and an algorithmic prototype we trace how the resulting habituation rewards happiness, efficiency, and uniformity at the expense of moodiness, messiness, and difference. Ultimately, we argue that going off scripts and embracing the “fuck up” can help resist technoliberalism.
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This paper is an author response to three commentaries, by Robert Kraut and Itamar Rosenn (2012), Barry Wellman (2012) and Mark van Vugt (2012), on our article entitled 'Relationships and the social brain: Integrating psychological and evolutionary perspectives' (Sutcliffe, Dunbar, Binder, & Arrow, 2012).
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We describe an interview-based data-collection procedure for social network analysis designed to aid gathering information about the people known by a respondent and reduce problems with data integrity and respondent burden. This procedure, a participant-aided network diagram (sociogram), is an extension of traditional name generators. Although such a diagram can be produced through computer-assisted programs for interviewing (CAPIs) and low technology (i.e., paper), we demonstrate both practical and methodological reasons for keeping high technology in the lab and low technology in the field. We provide some general heuristics that can reduce the time needed to complete a name generator. We present findings from our Connected Lives field study to illustrate this procedure and compare to an alternative method for gathering network data.
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There is some panic in the United States about a possible decline in social connectivity. The authors used two American national surveys to analyze how changes in the number of friends are related to changes in Internet use. The authors found that friendships continue to be abundant among adult Americans between the ages of 25 to 74 and that they grew from 2002 to 2007. This trend is similar among Internet nonusers, light users, moderate users, and heavy users and across communication contexts: offline, virtual only, and migratory from online to offline. Heavy users are particularly active, having the most friends both online and offline. Intracohort change consistently outweighs cohort replacement in explaining overall growth in friendship.
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We apply our network scale-up model to estimate the number of people in the U.S. who know someone who experienced the terrorist attacks of September 11, 2001 and the number of people who know someone who knows someone who experienced those attacks.
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In contrast to technologically deterministic approaches that focus on how communication technology affects social relationships, this paper examines how individuals draw on a variety of commonly used communication media in conjunction with in-person contact to stay connected to their personal networks. I term this use of multiple communication media the 'personal communication system'. Findings are based on a random sample telephone survey of 2200 adults living throughout the continental USA. Descriptive statistics show that despite the popularity of email and mobile phones, in-person and landline phone contact are still the most common ways of connecting with personal networks. Multivariate analysis reveals a more complex picture of media use, showing that the extent to which each medium is used varies to differing degrees with the size and diversity of personal networks. Hierarchical cluster analysis is used to explore the possibility that individuals may have different types of personal communication systems. Results show only two distinct clusters: those who draw heavily on all types of media to connect with their personal networks and those who draw less heavily on all types of media. Heavy communicators typically have larger and more diverse personal networks than light communicators. When taken together, the results presented in this paper suggest that rather than radically altering relationships, communication technology is embedded in social networks as part of a larger communication system that individuals use to stay socially connected.
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Psychological studies of relationships tend to focus on specific types of close personal relationships (romantic, parent-offspring, friendship) and examine characteristics of both the individuals and the dyad. This paper looks more broadly at the wider range of relationships that constitute an individual's personal social world. Recent work on the composition of personal social networks suggests that they consist of a series of layers that differ in the quality and quantity of relationships involved. Each layer increases relationship numbers by an approximate multiple of 3 (5-15-50-150) but decreasing levels of intimacy (strong, medium, and weak ties) and frequency of interaction. To account for these regularities, we draw on both social and evolutionary psychology to argue that relationships at different layers serve different functions and have different cost-benefit profiles. At each layer, the benefits are asymptotic but the costs of maintaining a relationship at that level (most obviously, the time that has to be invested in servicing it) are roughly linear with the number of relationships. The trade-off between costs and benefits at a given level, and across the different types of demands and resources typical of different levels, gives rise to a distribution of social effort that generates and maintains a hierarchy of layered sets of relationships within social networks. We suggest that, psychologically, these trade-offs are related to the level of trust in a relationship, and that this is itself a function of the time invested in the relationship.
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Using 2006 General Social Survey data, the authors compare levels of segregation by race and along other dimensions of potential social cleavage in the contemporary United States. Americans are not as isolated as the most extreme recent estimates suggest. However, hopes that "bridging" social capital is more common in broader acquaintanceship networks than in core networks are not supported. Instead, the entire acquaintanceship network is perceived by Americans to be about as segregated as the much smaller network of close ties. People do not always know the religiosity, political ideology, family behaviors, or socioeconomic status of their acquaintances, but perceived social divisions on these dimensions are high, sometimes rivaling racial segregation in acquaintanceship networks. The major challenge to social integration today comes from the tendency of many Americans to isolate themselves from others who differ on race, political ideology, level of religiosity, and other salient aspects of social identity.
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Respondent-driven sampling (RDS) is a network-based technique for estimating traits in hard-to-reach populations, for example, the prevalence of HIV among drug injectors. In recent years RDS has been used in more than 120 studies in more than 20 countries and by leading public health organizations, including the Centers for Disease Control and Prevention in the United States. Despite the widespread use and growing popularity of RDS, there has been little empirical validation of the methodology. Here we investigate the performance of RDS by simulating sampling from 85 known, network populations. Across a variety of traits we find that RDS is substantially less accurate than generally acknowledged and that reported RDS confidence intervals are misleadingly narrow. Moreover, because we model a best-case scenario in which the theoretical RDS sampling assumptions hold exactly, it is unlikely that RDS performs any better in practice than in our simulations. Notably, the poor performance of RDS is driven not by the bias but by the high variance of estimates, a possibility that had been largely overlooked in the RDS literature. Given the consistency of our results across networks and our generous sampling conditions, we conclude that RDS as currently practiced may not be suitable for key aspects of public health surveillance where it is now extensively applied.
Consequential strangers Personal networks and the personal communication system: Using multiple communication media to connect with personal networks
  • M Blau
  • K Fingerman
Blau, M., & Fingerman, K. (2009). Consequential strangers. New York: Norton. Boase, J. (2008). Personal networks and the personal communication system: Using multiple communication media to connect with personal networks. Information, Communication and Society, 11(4), 490–508.
The Colors of closeness. Paper presented at the International Sunbelt Social Network Conference
  • M Godbout
  • T Kennedy
  • B Wellman
  • Y Zhang
Godbout, M., Kennedy, T., Wellman, B., & Zhang, Y. (2011). The Colors of closeness. Paper presented at the International Sunbelt Social Network Conference, St. Pete Beach, FL, USA.
Personal communities
  • V Chua
  • J Madej
  • B Wellman
Chua, V., Madej, J., & Wellman, B. (2011). Personal communities. In P. Carrington & J. Scott (Eds.), Handbook of social network analysis (pp. 101–115). London: Sage.
Personal networks and the personal communication system: Using multiple communication media to connect with personal networks
  • Boase