Content uploaded by Stefan Stieglitz
Author content
All content in this area was uploaded by Stefan Stieglitz on May 24, 2014
Content may be subject to copyright.
A preview of the PDF is not available
Emotions and Information Diffusion in Social Media — Sentiment of Microblogs and Sharing Behavior
Abstract and Figures
As a new communication paradigm, social media has promoted information dissemination in social networks. Previous research has identified several content-related features as well as user and network characteristics that may drive information diffusion. However, little research has focused on the relationship between emotions and information diffusion in a social media setting. In this paper, we examine whether sentiment occurring in social media content is associated with a user's information sharing behavior. We carry out our research in the context of political communication on Twitter. Based on two data sets of more than 165,000 tweets in total, we find that emotionally charged Twitter messages tend to be retweeted more often and more quickly compared to neutral ones. As a practical implication, companies should pay more attention to the analysis of sentiment related to their brands and products in social media communication as well as in designing advertising content that triggers emotions.
Figures - uploaded by Stefan Stieglitz
Author content
All figure content in this area was uploaded by Stefan Stieglitz
Content may be subject to copyright.
... Previous work has explored the role of negativity in driving online behaviour. In particular, negative language in online content has been linked to user engagement, that is, sharing activities 22,[34][35][36][37][38][39] . As such, negativity embedded in online content explains the speed and virality of online diffusion dynamics (for example, response time, branching of online cascades) 7,34,35,37,[39][40][41] . ...
... In particular, negative language in online content has been linked to user engagement, that is, sharing activities 22,[34][35][36][37][38][39] . As such, negativity embedded in online content explains the speed and virality of online diffusion dynamics (for example, response time, branching of online cascades) 7,34,35,37,[39][40][41] . Further, online stories from social media perceived as negative garner more reactions (for example, likes, Facebook reactions) 42,43 . ...
... This may be because of the social and informational value that high-arousal emotions such as anger and fear hold-both could alert others in one's group to threats, and paying preferential attention and recognition to these emotions could help the group survive 27,32 . This may also be why in the current age, people are more likely to share and engage with online content that is embedding anger, effects for specific topics such as political communication and economics 34,[48][49][50][51][52] . Informed by this, we hypothesized an effect of negative words on online news consumption. ...
Online media is important for society in informing and shaping opinions, hence raising the question of what drives online news consumption. Here we analyse the causal effect of negative and emotional words on news consumption using a large online dataset of viral news stories. Specifically, we conducted our analyses using a series of randomized controlled trials (N = 22,743). Our dataset comprises ~105,000 different variations of news stories from Upworthy.com that generated ∼5.7 million clicks across more than 370 million overall impressions. Although positive words were slightly more prevalent than negative words, we found that negative words in news headlines increased consumption rates (and positive words decreased consumption rates). For a headline of average length, each additional negative word increased the click-through rate by 2.3%. Our results contribute to a better understanding of why users engage with online media.
... In the field of rumor spreading, data from Twitter has been used to explore the opinion formation processes [11], opinion polarization [12][13][14], emergence of echo chambers [12,[15][16][17], misinformation diffusion [18][19][20][21], or viral spreading of memes [22,23]. Other interesting works have measured sentiment metrics [24,25], state of opinions [26,27], or tracked the evolution of certain topics or conflicts [28][29][30]. ...
Social networks constitute an almost endless source of social behavior information. In fact, sometimes the amount of information is so large that the task to extract meaningful information becomes impossible due to temporal constrictions. We developed an artificial-intelligence-based method that reduces the calculation time several orders of magnitude when conveniently trained. We exemplify the problem by extracting data freely available in a commonly used social network, Twitter, building up a complex network that describes the online activity patterns of society. These networks are composed of a huge number of nodes and an even larger number of connections, making extremely difficult to extract meaningful data that summarizes and/or describes behaviors. Each network is then rendered into an image and later analyzed using an AI method based on Convolutional Neural Networks to extract the structural information.
... En el momento en el que los públicos se exponen a informaciones menos positivas, consecuentemente los comentarios publicados son más negativos, y lo mismo sucede en el sentido opuesto (Wollebaek et al., 2019). Este hecho también se manifiesta en lo que se refiere al intercambio de contenido, Stieglitz & Dang-Xuan (2013), Bail (2016) y Brady, Wills, Jost, Tucker & Van Bavel (2017 indican que es más probable que los mensajes que están cargados de emociones en las redes sociales, tienen mayor probabilidad de ser compartidos que aquellos mensajes neutrales. Por su parte, Lottridge & Bentley (2018) señalan que expresar enfado hacia un evento en particular es una motivación clave para compartir noticias en redes sociales como Twitter y Reddit. ...
Las redes sociales se han convertido en un medio imprescindible de comunicación y han modificado el concepto de comunicación política. En la actualidad, las redes provocan un impacto importante en las campañas electorales a nivel mundial, y, por ello, los últimos procesos electorales en el contexto latinoamericano son un espacio idóneo para el análisis por la volatilidad y riqueza de la competición político-electoral, así como por el hecho de tener la capacidad de influir en el intercambio de información política a través de las distintas emociones que despiertan en las audiencias. Este trabajo es un estudio sistematizado de la comunicación en redes sociales llevada a cabo durante la primera vuelta del proceso electoral de Costa Rica de 2022 (6 de febrero). Los datos se recogieron a través del Observatorio de Comunicación Digital de Medios de la Universidad Latina de Costa Rica a través de las herramientas de social listening de Minerva Data, Adspend de Kantar IBOPE Media y Mention, con el objetivo de mostrar cuáles son las tendencias de conversación digital en esta campaña, en un proceso electoral sin precedentes con 25 candidatos presidenciales. El seguimiento de los reportes realizados por el Observatorio de Comunicación Digitalmuestran la evolución del comportamiento del electorado en términos de interacción, sentimiento, temática e intención de voto, durante la primera vuelta del proceso electoral 2022, así como la dinámica general percibida en el ámbito de las redes sociales y web pública.
... Our findings on emotional expressions provide two useful insights. First, the results reveal that it can be beneficial on social media to explicitly express one's emotions than keeping them contained, which is consistent with the findings in prior research (Berger and Milkman 2012;Stieglitz and Dang-Xuan 2013). Second, although emotion expressed on Instagram is relatively more positive, when expressed, negative emotion has a stronger impact on boosting consumer responses. ...
Despite firms’ continued interest in using influencers to reach their target consumers, academic and practical insights are limited on what levers an influencer can use to enhance audience engagement using their posts. We demonstrate that posting stories with or about people whom they share close ties with—such as family, friends, and romantic partners—can be one effective lever. Content that incorporates close social ties can be effective for several reasons: it may increase perceptions of authenticity, enhance perceived similarity, increase the perception that the influencer possesses more warmth, and could satisfy viewers’ interpersonal curiosity. We analyze texts and photographs of 55,631 posts of 763 influencers on Instagram, and after controlling for several variables, we find robust support that consumers “like” posts that reference close social ties. Further, this effect enhances when first-person pronouns are used to describe special moments with these close ties. We supplement the Instagram data with an experimental approach and confirm the relationship between close ties and consumer engagement. Managerially, this is a useful insight as we also show that sponsored posts tend to be perceived negatively compared to non-sponsored posts, yet, embedding social ties on the sponsored posts can mitigate consumers’ negative responses.
... 52,53 Especially, during uncertain crises like pandemics, tweets that contain aggressive expressions of distress can spread high arousal of negative emotions on a collective level. 54,55 The networked public would then search for the reason behind their distressful emotional state, sometimes landing on misleading conclusions like conspiracy theories. Moreover, cultural attractor theory suggests that certain content properties (e.g., content eliciting threat and danger) play critical roles in the distribution of cultural variants (e.g., beliefs, narratives, misinformation). ...
Since the breakout of COVID-19 in late 2019, various conspiracy theories have spread widely on social media and other channels, fueling misinformation about the origins of COVID-19 and the motives of those working to combat it. This study analyzes tweets (N = 313,088) collected over a 9-month period in 2020, which mention a set of well-known conspiracy theories about the role of Bill Gates during the pandemic. Using a topic modeling technique (i.e., Biterm Topic Model), this study identified ten salient topics surrounding Bill Gates on Twitter, and we further investigated the interactions between different topics using Granger causality tests. The results demonstrate that emotionally charged conspiratorial narratives are more likely to breed other conspiratorial narratives in the following days. The findings show that each conspiracy theory is not isolated by itself. Instead, they are highly dynamic and interwoven. This study presents new empirical insights into how conspiracy theories spread and interact during crises. Practical and theoretical implications are also discussed.
The NATO STO HFM-ET-356 performed an assessment of the Science and Technologies (S&T) required to mitigate and defend against Cognitive Warfare (CogWar). CogWar has emerged replete with security challenges due to its invasive and invisible nature and where the goal is to exploit facets of cognition to disrupt, undermine, influence, or modify human decisions (proposed by HFM-ET-356). CogWar represents the convergence of a wide range of advanced technologies along with human factors, used by NATO’s adversaries in the 21st century battlespace. CogWar is a risk to global defence and security and threatens human decision making. The ET-356 proposed a S&T Road map to guide NATO and Allied Partners in future research activities and investments. The proposed Road map is based on a “House Model,” and linked to the Observe, Orient, Decide, and Act (OODA) decision cycle. The Model represents seven main S&T knowledge areas and enablers that are cross-cutting related: Pillars: Cognitive Neuroscience, Cognitive and Behavioral Science, Social and Cultural Science; and Bars: Situational Awareness and Sensemaking, Cognitive Effects, modus operandi, and Technology and Force Multipliers. This work underpins the NATO Warfighting Capstone Concept and its Warfare Development Initiative Cognitive Superiority, and the NATO Strategic Concept 2022.
As a significant human behavior, disaster information behavior may operate as a catalyst for affecting the evolution of disaster occurrences in social-ecological systems and the sustainability of social systems. Yet little research has been carried out on this subject, particularly on the information behavior of major natural disasters. Based on the case of the 7.20 Henan heavy rain flood disaster, this study constructs an information behavior composite index from the four dimensions of temporal, spatial, content, and behavioral agents and statistically identifies and quantifies the characteristics and differences of disaster information behavior in social media. The results are as follows. (1) Disaster information behaviors have an obvious life cycle with three phases, essentially following the “formation-development-extinction” process; disaster areas, near-disaster areas, and economically and technologically developed areas exhibit higher levels of information behavior. (2) A total of 47% of the content is related to the case, while 53% is unrelated; the most related microblogs (43.88%) were about “Disaster response/relief”. (3) Females (54.19%) engage in more information behavior than males (45.81%) and they also exhibit more positive behavior; the 20–29-year-old age group is dominated by positive and neutral comments with the highest level of information behavior, whereas the lowest level of information behavior occurs in the 50+ age group; neutral and irrelevant comments in the 30–49-year-old age group dominated. This case study enables a scientific understanding of the necessity of information dissemination for disaster prevention and mitigation and further demonstrates the hazard, psychological distance, societal, and individual factors that all affect how disaster information behaves and performs differently.
With the increasing attention paid to environmental protection and sustainable development in various countries worldwide, the relationship between local government competition and environmental governance has become more subtle and complex. This paper provides new insight into their relationship based on public value theory and media sentiment perspective. Utilizing panel data from 2012 to 2019 in 216 cities in China, this study integrated Data Envelopment Analysis, Conflicting Attitudes Model, Computer-Aided Text Analysis, and machine learning-based sentiment analysis, as well as nonlinear mediation model to empirically test the relationships among local governments’ competition pressure, public value conflict, media sentiments, and environmental governance performance. The study found that: (1) Competition pressure and environmental governance performance exist in a “U-curved” relationship. (2) The core mechanism of the above relationship lies in the mediating role of public value conflict. Within a specific range, the public value conflict faced by local governments increases as competition pressure increases. This conflict would push local governments into a dilemma and induce them to commit misconduct. However, when competition pressure exceeds this range, the public value conflict faced by local governments will be weakened, leading environmental governance performance to rebound. (3) Negative media sentiments significantly alleviate the negative impact of public value conflict on environmental governance performance. This study helps researchers and policymakers recognize government competition’s influence on environmental governance from a public value perspective, with further exploration and confirmation of the moderating role of media sentiments. It also provides theoretical and policy enlightenment for rethinking the behavior logic of local government and solving the dilemma of local government environmental governance.
In this study we investigate how social media shape the
networked public sphere and facilitate communication between
communities with different political orientations. We
examine two networks of political communication on Twitter,
comprised of more than 250,000 tweets from the six
weeks leading up to the 2010 U.S. congressional midterm
elections. Using a combination of network clustering algorithms
and manually-annotated data we demonstrate that the
network of political retweets exhibits a highly segregated partisan
structure, with extremely limited connectivity between
left- and right-leaning users. Surprisingly this is not the case
for the user-to-user mention network, which is dominated by
a single politically heterogeneous cluster of users in which
ideologically-opposed individuals interact at a much higher
rate compared to the network of retweets. To explain the distinct
topologies of the retweet and mention networks we conjecture
that politically motivated individuals provoke interaction
by injecting partisan content into information streams
whose primary audience consists of ideologically-opposed
users. We conclude with statistical evidence in support of this
hypothesis.
In recent years, social media are said to have an impact on the public discourse and communication in the society. In particular, social media are increasingly used in political context. More recently, microblogging services (e.g., Twitter) and social network sites (e.g., Facebook) are believed to have the potential for increasing political participation. While Twitter is an ideal platform for users to spread not only information in general but also political opinions publicly through their networks, political institutions (e.g., politicians, political parties, political foundations, etc.) have also begun to use Facebook pages or groups for the purpose of entering into direct dialogues with citizens and enabling political discussions. Previous studies have shown that from the perspective of political institutions, there is a need to continuously collect, monitor, analyze, summarize, and visualize politically relevant information from social media. These activities, which are subsumed under “social media analytics,” are considered difficult tasks due to a large numbers of different social media platforms and large amount as well as complexity of information and data. Systematic tracking and analysis approaches along with appropriate methods and techniques in political domain are still lacking. In this paper, we propose a framework for social media analytics in political context. More specifically, our framework summarizes different politically relevant analyses from the perspective of political institutions and according scientific methodologies that could be applied to analyze political communication in social media.
In recent years, political parties and politicians have begun to use public Facebook "pages" not only for the purpose of self-presentation but also to aim at entering into direct dialogues with citizens and enabling political discussions. Not only the owner of the page but also any people who are politically interested can create politically relevant postings on the "Wall" of the page. These "Wall posts" often exhibit sentiment associated with certain political topics, political parties or politicians. In this paper, we seek to examine whether sentiment occurring in Wall posts on public political Facebook pages has an effect on feedback in terms of the quantity of triggered comments. Based on a data set of 5,626 Wall posts from Facebook pages of German political parties and politicians, we find different significant relationships between the quantity of words indicating positive and negative emotions in a Wall post and the number of its corresponding comments. Furthermore, our results show that positive as well as negative emotions might diffuse in the subsequent comments.
In this paper, we examine whether sentiment of political blog entries is associated with increased feedback in terms of the quantity of triggered comments and whether the diffusion of sentiment might take place in the political blogosphere. Based on a data set of approximately 17,000 blog entries from the 60 most important German political blogs, we find that blog entries with either more positive or more negative overall sentiment tend to receive significantly more comments compared to sentiment-neutral or mixed-sentiment entries. Furthermore, our results show that positive as well as negative emotions might diffuse in the subsequent comments to corresponding blog entries.
Among the many so-called microblogging services that allow their users to describe their current status in short posts, Twitter is probably among the most popular and well known. Since its launch in 2006, Twitter use has evolved and is increasingly used in a variety of contexts. This article utilizes emerging online tools and presents a rationale for data collection and analysis of Twitter users. The suggested approach is exemplified with a case study: Twitter use during the 2010 Swedish election. Although many of the initial hopes for e-democracy appear to have gone largely unfulfilled, the successful employment of the internet during the 2008 US presidential campaign has again raised voices claiming that the internet, and particularly social media applications like Twitter, provides interesting opportunities for online campaigning and deliberation. Besides providing an overarching analysis of how Twitter use was fashioned during the 2010 Swedish election campaign, this study identifies different user types based on how high-end users utilized the Twitter service. By suggesting a novel approach to the study of microblogging and by identifying user types, this study contributes to the burgeoning field of microblog research and gives specific insights into the practice of civic microblogging.
: This article examines the potential for Internet discussion boards to be a vehicle for political deliberation through a case study of the BC Votes discussion board during British Columbia’s 2001 provincial election. Research reveals that the board was dominated by a relatively small number of users and that the favourite discussion topics were not issues but how parties and leaders were performing. The authors conclude that the perception of ideological homogeneity in online discussion may be overstated and that the first post in a discussion thread has an important agenda-setting function. They also find that the relative newness of discussion boards may play a role in shaping the nature of discussion there.
Resume : Afin d’examiner le potentiel des babillards electroniques comme vehicules de debats politiques, cet article offre une etude de cas sur le babillard BC Votes lors des elections provinciales en Colombie-Britannique en 2001. Les auteurs demontrent que relativement peu d’usagers dominaient le babillard et que les sujets preferes de discussion ne touchaient pas aux enjeux de la campagne electorale, mais plutot a la performance des parties politiques et de leurs leaders. Les auteurs concluent que l’homogeneite ideologique des babillards electroniques n’est peut-etre qu’une perception exageree et que souvent le ton polemique du debat est dicte par le premier message dans un fil de discussion. Les auteurs concluent aussi que le caractere relativement nouveau des babillards reflete sur la specificite de la discussion qui s’y deroule.
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.