An agent-based model for emotion contagion and competition in online social media
Authored by Rui Fan, Ke Xu, Jichang Zhao
Date Published: 2018
DOI: 10.1016/j.physa.2017.12.086
Sponsors:
Chinese National Natural Science Foundation
Canada Foundation for Innovation (CFI)
State Key Lab of Software Development Environment
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Model Code URLs:
Model code not found
Abstract
Recent studies suggest that human emotions diffuse in not only
real-world communities but also online social media. However, a
comprehensive model that considers up-todate findings and multiple
online social media mechanisms is still missing. To bridge this vital
gap, an agent-based model, which concurrently considers emotion
influence and tie strength preferences, is presented to simulate the
emotion contagion and competition. Our model well reproduces patterns
observed in the empirical data, like anger's preference on weak ties,
anger-dominated users' high vitalities and angry tweets' short retweet
intervals, and anger's competitiveness in negative events. The
comparison with a previously presented baseline model further
demonstrates its effectiveness in modeling online emotion contagion. It
is also surprisingly revealed by our model that as the ratio of anger
approaches joy with a gap less than 12\%, anger will eventually dominate
the online social media and arrives the collective outrage in the cyber
space. The critical gap disclosed here can be indeed warning signals at
early stages for outrage control. Our model would shed lights on the
study of multiple issues regarding emotion contagion and competition in
terms of computer simulations. (C) 2017 Elsevier B.V. All rights
reserved.
Tags
Agent-based model
behavior
networks
information
Happiness
Attention
Emotion contagion
Emotion competition
Emotion
correlation
Tie strength