Computer Science – Social and Information Networks
Scientific paper
2011-10-23
Computer Science
Social and Information Networks
Scientific paper
Background: We study mechanisms underlying the collective emotional behavior of Bloggers by using the agent-based modeling and the parameters inferred from the related empirical data. Methodology/Principal Findings: A bipartite network of emotional agents and posts evolves through the addition of agents and their actions on posts. The emotion state of an agent,quantified by the arousal and the valence, fluctuates in time due to events on the connected posts, and in the moments of agent's action it is transferred to a selected post. We claim that the indirect communication of the emotion in the model rules, combined with the action-delay time and the circadian rhythm extracted from the empirical data, can explain the genesis of emotional bursts by users on popular Blogs and similar Web portals. The model also identifies the parameters and how they influence the course of the dynamics. Conclusions: The collective behavior is here recognized by the emergence of communities on the network and the fractal time-series of their emotional comments, powered by the negative emotion (critique). The evolving agents communities leave characteristic patterns of the activity in the phase space of the arousal--valence variables, where each segment represents a common emotion described in psychology.
Mitrović Marija
Tadic Bosiljka
No associations
LandOfFree
Patterns of Emotional Blogging and Emergence of Communities: Agent-Based Model on Bipartite Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Patterns of Emotional Blogging and Emergence of Communities: Agent-Based Model on Bipartite Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Patterns of Emotional Blogging and Emergence of Communities: Agent-Based Model on Bipartite Networks will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-526905