Flow of Emotional Messages in Artificial Social Networks

Chmiel, Anna; Hołyst, Janusz A.

doi:10.1142/s012918311001535x

Cited by 11 publications

(13 citation statements)

References 33 publications

(16 reference statements)

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“…Our analysis provides a better understanding of affective interactions between large numbers of people and is an important step towards the development of models of collective emotions in cyberspace [8,24,[27][28][29][30][31]. By involving collective phenomena, these patterns go beyond the complexity of the nested intra-and inter-individual feedback loops in face-to-face communication [32].…”

Section: Discussionmentioning

confidence: 99%

Collective Emotions Online and Their Influence on Community Life

et al. 2011

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BackgroundE-communities, social groups interacting online, have recently become an object of interdisciplinary research. As with face-to-face meetings, Internet exchanges may not only include factual information but also emotional information – how participants feel about the subject discussed or other group members. Emotions in turn are known to be important in affecting interaction partners in offline communication in many ways. Could emotions in Internet exchanges affect others and systematically influence quantitative and qualitative aspects of the trajectory of e-communities? The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. However, it is not clear if emotions in e-communities primarily derive from individual group members' personalities or if they result from intra-group interactions, and whether they influence group activities.Methodology/Principal FindingsHere, for the first time, we show the collective character of affective phenomena on a large scale as observed in four million posts downloaded from Blogs, Digg and BBC forums. To test whether the emotions of a community member may influence the emotions of others, posts were grouped into clusters of messages with similar emotional valences. The frequency of long clusters was much higher than it would be if emotions occurred at random. Distributions for cluster lengths can be explained by preferential processes because conditional probabilities for consecutive messages grow as a power law with cluster length. For BBC forum threads, average discussion lengths were higher for larger values of absolute average emotional valence in the first ten comments and the average amount of emotion in messages fell during discussions.Conclusions/SignificanceOverall, our results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities.

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Section: Discussionmentioning

confidence: 99%

Collective Emotions Online and Their Influence on Community Life

et al. 2011

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“…For example, the network of posts and comments in various blog sites [19] has a strong community structure that could be created by emotional discussions. The effect of emotions in creating and reshaping social contacts was also modeled in artificial social networks [20].…”

Section: Introductionmentioning

confidence: 99%

An agent-based model of collective emotions in online communities

2010

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We develop an agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agent's individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a superlinear feedback between the information field and the agent's arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities.

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“…Simulations, based on game theory, have reproduced this behavior, depending on the ratio of opposing agents in the simulated group. Extending the approach beyond opinions, Schweitzer and Garcia [17] proposed an agent-based model of collective emotions in online communities, while Chmiel and Holyst [18] proposed a model of social network evolution driven by the exchange of emotional messages. activity statistics as well as emotional content.…”

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Negative emotions boost user activity at BBC forum

Chmiel

Sobkowicz

Sienkiewicz

et al. 2011

Physica A: Statistical Mechanics and its Applications

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We present an empirical study of user activity in online BBC discussion forums, measured by the number of posts written by individual debaters and the average sentiment of these posts. Nearly 2.5 million posts from over 18 thousand users were investigated. Scale free distributions were observed for activity in individual discussion threads as well as for overall activity.The number of unique users in a thread normalized by the thread length decays with thread length, suggesting that thread life is sustained by mutual discussions rather than by independent comments. Automatic sentiment analysis shows that most posts contain negative emotions and the most active users in individual threads express predominantly negative sentiments. It follows that the average emotion of longer threads is more negative and that threads can be sustained by negative comments. An agent based computer simulation model has been used to reproduce several essential characteristics of the analyzed system. The model stresses the role of discussions between users, especially emotionally laden quarrels between supporters of opposite *

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Flow of Emotional Messages in Artificial Social Networks

Cited by 11 publications

References 33 publications

Collective Emotions Online and Their Influence on Community Life

Collective Emotions Online and Their Influence on Community Life

An agent-based model of collective emotions in online communities

Negative emotions boost user activity at BBC forum

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