Abstract
Quantitative analysis of the empirical data from online social networks reveals the occurrence of group dynamics in which the user’s emotions are involved. Full understanding of the underlying mechanisms, however, remains a challenging task. Using agent-based computer simulations, in this work we study the dynamics of emotional communications in online social networks. The rules that guide how the agents interact, are motivated by actual online social systems. The realistic network structure and some key parameters are inferred from the empirical dataset compiled from the MySpace social network. An agent’s emotional state is characterized by two variables representing emotional arousal—reactivity to stimuli, and valence—attractiveness or averseness, by which a commonly known emotion can be identified. Elevated arousal triggers an agent’s action. In the simulations, each message is identified as carrying an agent’s emotion along a network link; an aggregated and continuously aging impact of these messages on the recipient agent is considered. Our results indicate that group behavior may arise from individual emotional actions of agents; the collective states appear, which are characterized by temporal correlations and predominantly positive emotions, in analogy to the empirical system; the driving signal—rate of the user stepping into the online world—has a profound effect on building the coherent behaviors that are observed in online social networks. Moreover, our simulations suggest that spreading patterns may differ for the emotions with the entirely different positive and negative emotional content.
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References
Ahn, J., Gobron, S., Silvestre, Q., Thalmann, D.: Asymmetrical facial expressions based on an advanced interpretation of two-dimensional Russell’s emotional model. EPFL-CONF-164427. http://infoscience.epfl.ch/record/164427 (2010)
Amichai-Hamburger, Y.: Internet and personality. Comput. Hum. Behav. 18 (1), 1–10 (2002). doi:10.1016/S0747-5632(01)00034-6
Amichai-Hamburger, Y., Vinitzky, G.: Social network use and personality. Comput. Hum. Behav. 26 (6), 1289–1295 (2010). doi:10.1016/j.chb.2010.03.018
Bradley, M.M.: Natural selective attention: orienting and emotion. Psychophysiology 46 (1), 1–11 (2009). doi:10.1111/j.1469-8986.2008.00702.x
Bradley, M.M., Lang, P.J.: Affective norms for English words (ANEW): instruction manual and affective ratings. Technical Report C-1, University of Florida, Center for Research in Psychophysiology (1999)
Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Rev. Mod. Phys. 81, 591–646 (2009). doi:10.1103/RevModPhys.81.591
Cheung, C.M.K., Chiu, P.Y., Lee, M.K.O.: Online social networks: why do students use facebook? Comput. Hum. Behav. 27 (4), 1337–1343 (2011). doi:10.1016/j.chb.2010.07.028
Chmiel, A., Sienkiewicz, J., Thelwall, M., Paltoglou, G., Buckley, K., Kappas, A., Hołyst, J.A.: Collective emotions online and their influence on community life. PLoS ONE 6 (7), e22207 (2011). doi:10.1371/journal.pone.0022207
Coan, J.A., Allen, J.J.B (eds.): The Handbook of Emotion Elicitation and Assessment. Series in Affective Science. Oxford University Press, Oxford (2007)
Crane, R., Schweitzer, F., Sornette, D.: New power law signature of media exposure in human response waiting time distributions. Phys. Rev. E 81 (5), 056101 (2010). doi:10.1103/PhysRevE.81.056101
DiMaggio, P., Hargittai, E., Neuman, W.R., Robinson, J.P.: Social implications of the internet. Annu. Rev. Sociol. 27 (1), 307–336 (2001). doi:10.1146/annurev.soc.27.1.307
Dodds, P., Danforth, C.: Measuring the happiness of large-scale written expression: songs, blogs, and presidents. J. Happiness Stud. 11 (4), 441–456 (2010). doi:10.1007/s10902-009-9150-9
Garas, A., Garcia, D., Skowron, M., Schweitzer, F.: Emotional persistence in online chatting communities. Sci. Rep. 2, 402 (2012). doi:10.1038/srep00402
Garcia, D., Schweitzer, F.: Emotions in product reviews – empirics and models. In: Proceedings of 2011 IEEE International Conference on Privacy, Security, Risk, and Trust, and IEEE International Conference on Social Computing, PASSAT/SocialCom, pp. 483–488 (2011). doi:10.1109/PASSAT/SocialCom.2011.219)
Garcia, D., Garas, A., Schweitzer, F.: Positive words carry less information than negative words. EPJ Data Sci. 1 (1), 3 (2012). doi:0.1140/epjds3
Giles, M.: A world of connections - a special report on social networking. The Economist, p.16, January (2010)
Giles, J.: Social science lines up its biggest challenges. Nature 470, 18–19 (2011). doi:0.1038/470018a
Gligorijević, V., Skowron, M., Tadić, B.: Structure and stability of online chat networks built on emotion-carrying links. Physica A 392 (3), 538–543 (2013). doi:10.1016/j.physa.2012.10.003
Guimerà, R., Danon, L., Díaz-Guilera, A., Giralt, F., Arenas, A.: Self-similar community structure in a network of human interactions. Phys. Rev. E 68 (6), 065103 (2003). doi:10.1103/PhysRevE.68.065103
Johnson, N.F., Xu, C., Zhao, Z., Ducheneaut, N., Yee, N., Tita, G., Hui, P.M.: Human group formation in online guilds and offline gangs driven by a common team dynamic. Phys. Rev. E 79 (6), 066117 (2009). doi:10.1103/PhysRevE.79.066117
Kleinberg, J.: The convergence of social and technological networks. Commun. ACM 51 (11), 66–72 (2008). doi:10.1145/1400214.1400232
Kuppens, P., Oravecz, Z., Tuerlincky, F.: Feelings change: accounting for individual differences in the temporal dynamics of affect. J. Pers. Soc. Psychol. 99 (6), 1042–60 (2010). doi:10.1037/a0020962
Küster, D., Tsankova, E., Theunis, M., Kappas, A.: Measuring cyberemotions: how do bodily responses relate to the digital world? In: 7th Conference of the Media Psychology Division of the Deutsche Gesellschaft für Psychologie, Bremen, August (2011)
Malmgren, R.D., Stouffer, C.B., Campanharo, A.S.L.O., Amaral, L.A.: On universality in human correspondence activity. Science 325 (5948), 1696–1700 (2009). doi:10.1126/science.1174562
Mitrović, M., Tadić, B.: Bloggers behavior and emergent communities in blog space. Eur. Phys. J. B 73 (2), 293–301 (2010). doi:10.1140/epjb/e2009-00431-9
Mitrović, M., Tadić, B.: Patterns of emotional blogging and emergence of communities: agent-based model on bipartite networks (2011). http://arxiv.org/abs/1110.5057
Mitrović, M., Tadić, B.: Emergence and structure of cybercommunities. In: Thai, M.M., Pardalos, P. (eds.) Handbook of Optimization in Complex Networks: Theory and Applications. Springer Optimization and its Applications, vol. 57, pp. 209–227. Springer, New York (2012a). doi:10.1007/978-1-4614-0754-6_8
Mitrović, M., Tadić, B.: Dynamics of bloggers’ communities: bipartite networks from empirical data and agent-based modeling. Physica A 391 (21), 5264–5278 (2012b). doi:10.1016/j.physa.2012.06.004
Mitrović, M., Paltoglou, G., Tadić, B.: Networks and emotion-driven user communities at popular blogs. Eur. Phys. J. B 77 (4), 597–609 (2010). doi:10.1140/epjb/e2010-00279-x
Mitrović, M., Paltoglou, G., Tadić, B.: Quantitative analysis of bloggers’ collective behavior powered by emotions. J. Stat. Mech. 2011 (2), P02005 (2011). doi:10.1088/1742-5468/2011/02/P02005
Paltoglou, G., Theunis, M., Kappas, A., Thelwall, M.: Predicting emotional responses to long informal text. IEEE. Trans. Affect. Comput. 4 (1), 107–115 (2013). doi:10.1109/T-AFFC.2012.26
Rimé, B.: Emotion elicits the social sharing of emotion: theory and empirical review. Emot. Rev. 1 (1), 60–85 (2009). doi:10.1177/1754073908097189
Roca, C.P., Lozano, S., Arenas, A., Sánchez, A.: Topological traps control flow on real networks: the case of coordination failures. PLoS ONE 5 (12), e15210 (2010). doi:10.1371/journal.pone.0015210
Rodgers, J.L.: The epistemology of mathematical and statistical modeling: a quiet methodological revolution. Am. Psychol. 65 (1), 1–12 (2010). doi:10.1037/a0018326
Russell, J.A.: A circumplex model of affect. J. Pers. Soc. Psychol. 39 (6), 1161–1178 (1980). doi:10.1037/h0077714
Ryan, T., Xsenos, S.: Who uses Facebook? An investigation into the relationship between the big five, shyness, narcissism, loneliness, and facebook usage. Comput. Hum. Behav. 27 (5), 1658–1664 (2011). doi:10.1016/j.chb.2011.02.004
Scherer, K.R.: What are emotions? And how can they be measured? Soc. Sci. Inf. 44 (4), 695–729 (2005). doi:10.1177/0539018405058216
Schweitzer, F.: Brownian Agents and Active Particles. Collective Dynamics in the Natural and Social Sciences, 1st edn. Springer Series in Synergetics. Springer, Berlin (2003). 10.1007/978-3-540-73845-9
Schweitzer, F., Garcia, D.: An agent-based model of collective emotions in online communities. Eur. Phys. J. B 77 (4), 533–545 (2010). doi:10.1140/epjb/e2010-00292-1
Šuvakov, M., Mitrović, M., Gligorijević, V., Tadić, B.: How the online social networks are used: dialogues-based structure of Myspace. J. R. Soc. Interface 10 (79), 20120819 (2012). doi:10.1098/rsif.2012.0819
Šuvakov, M., Garcia, D., Schweitzer, F., Tadić, B.: Agent-based simulations of emotion spreading in online social networks (2012). http://arxiv.org/abs/1205.6278
Szell, M., Thurner, S.: Measuring social dynamics in a massive multiplayer online game. Soc. Networks 32 (4), 313–329 (2010). doi:10.1016/j.socnet.2010.06.001
Szell, M., Lambiotte, R., Thurner, S.: Multirelational organization of large-scale social networks in an online world. Proc. Natl. Acad. Sci. USA 107 (31), 13636–13641 (2010). doi:10.1073/pnas.1004008107
Tadić, B.: Modeling behavior of Web users as agents with reason and sentiment. In: Kora, A.B. (ed.) Advances in Computational Modeling Research: Theory, Developments and Applications, pp. 177–186. Novapublishing, New York (2013)
Tadić, B., Šuvakov, M.: Can human-like bots control collective mood: agent-based simulations of online chats. J. Stat. Mech. Theory E 2013 (10), P10014 (2013). doi:10.1088/1742-5468/2013/10/P10014
Tadić, B., Malarz, K., Kułakowski, K.: Magnetization reversal in spin patterns with complex geometry. Phys. Rev. Lett. 94, 137204 (2005). doi:10.1103/PhysRevLett.94.137204
Tadić, B., Rodgers, G.J., Thurner, S.: Transport on complex networks: flow, jamming and optimization. Int. J. Bifurcat. Chaos 17 (7), 2363–2385 (2007). doi:10.1142/S0218127407018452
Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., Kappas, A.: Sentiment strength detection in short informal text. J. Am. Soc. Inf. Sci. Technol. 61 (12), 2544–2558 (2010). doi:10.1002/asi.21416
van Rijsbergen, C.J., Robertson, S.E., Porter, M.F.: New Models in Probabilistic Information Retrieval, Computer Laboratory. University of Cambridge, Cambridge (1980)
Acknowledgements
The research leading to these results has received funding from the European Community’s Seventh Framework Programme FP7-ICT-2008-3 under grant agreement no 231323 and the project P-10044-3. B.T. is grateful for support from the national program P1-0044 of the Research Agency of the Republic of Slovenia and COST-TD1210 action. M.Š. also thanks the national research projects ON171037 and III41011 of the Republic of Serbia.
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Tadić, B., Šuvakov, M., Garcia, D., Schweitzer, F. (2017). Agent-Based Simulations of Emotional Dialogs in the Online Social Network MySpace. In: Holyst, J. (eds) Cyberemotions. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-43639-5_11
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