2012/05/29 by Milovan Šuvakov, David Garcia, David García +6 · 3 citations
Computer Science · Physics and Astronomy · Social Sciences · #Complex Network Analysis Techniques #Evolutionary Game Theory and Cooperation #FOS: Computer and information sciences #FOS: Physical sciences #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #cs.SI #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1205.6278
21 pages, 13 figures
arxiv created 2012/05/29 · openalex publication_date 2012/05/29 · arxiv updated 2012/05/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Quantitative analysis of empirical data from online social networks reveals group dynamics in which emotions are involved (Šuvakov et al). Full understanding of the underlying mechanisms, however, remains a challenging task. Using agent-based computer simulations, in this paper we study dynamics of emotional communications in online social networks. The rules that guide how the agents interact are motivated, and the realistic network structure and some important parameters are inferred from the empirical dataset of MySpace social network. Agent's emotional state is characterized by two variables representing psychological arousal---reactivity to stimuli, and valence---attractiveness or aversiveness, by which common emotions can be defined. Agent's action is triggered by increased arousal. High-resolution dynamics is implemented where each message carrying agent's emotion along the network link is identified and its effect on the recipient agent is considered as continuously aging in time. Our results demonstrate that (i) aggregated group behaviors may arise from individual emotional actions of agents; (ii) collective states characterized by temporal correlations and dominant positive emotions emerge, similar to the empirical system; (iii) nature of the driving signal---rate of user's stepping into online world, has profound effects on building the coherent behaviors, which are observed for users in online social networks. Further, our simulations suggest that spreading patterns differ for the emotions, e.g., "enthusiastic" and "ashamed", which have entirely different emotional content. \bf All data used in this study are fully anonymized.