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Understanding E-Herding and Behavioral Influence in Online Social Networks

This study examines the emergent behaviors and states of networks, particularly focusing on e-herding and behavioral influence within platforms like Twitter and Facebook. By analyzing the dynamics of user interactions—such as messaging, following, and tweeting—this research aims to identify factors that drive online and offline behaviors. The analysis incorporates empirical and simulated data to explore the psychological determinants behind user engagement, including time of day and the salience of topics. Insights from this work could enhance understanding of social media dynamics and user behavior.

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Understanding E-Herding and Behavioral Influence in Online Social Networks

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  1. Empirical Simulated Networks Twitter [in virtuo] Fb[in virtuo] Treema..[in virtuo] Work [in vivo] Riot [in vivo] … SON-M approach System/Network emergent behaviour & states E-herding + Behavioural Influence Nodes Twitter [in virtuo] Fb[in virtuo] Treema..[in virtuo] Work [in vivo] Riot [in vivo] … Behavioural Influence Element/Node manifest behaviour & states intra & inter psychic

  2. search & find #tag or @pap write message to @pap read message from @pap Node behaviors: twitter messaging search & find (un)following Online/offline @a logon / logoff @b @b (un)follows @a updating @b profile @a profile tweeting reading profiles reading new:#tag ret:#tag ∆ret:#tag plain tweet no tweet tweets eHerd? at system level, through time eHerding?

  3. intra & inter psychic DETERMINANTS Node behaviors& possible determinants: twitter DATA internal (twitter) BEHAVIORS (twitter) DATA external arousal Proxy: significant increase in tweets survey logon / logoff habits Proxy: time of day,…. survey reading tweets salience of topic Proxy: search history, past tweets, survey, news hype tweeting cognitive capacity See article Wen See article Wen search & find gender 5 5 updating profile age 6 6 reading profiles perceived events Proxy: search history, past tweets, survey, news hype messaging need to interact Proxy: frequency tweets and messaging survey (un)following trust Proxy: following? survey? need to belong Proxy: correspondence followees & followers ??? survey ??? ??? ???

  4. Diameter node = univariate Thickness arrow= correlation strength T: longitudinal or S: cross sectional T1 or S1 T2 or S2 T3 or S3 p1,1 p1,2 p1,3 System Behavior: twitter p3,1 p3,2 p2,3 p3,3 p2,1 p2,2 p4,1 p5,1 p5,2 p5,3 p4,2 p4,3 p7,1 p7,2 p7,3 p6,1 p6,2 p6,3 p1,i : outgoing connections p2,i : distribution #tags p3,i : volume #tag(s) …. System Tor S =(subset: #tags and/or @nodes)

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