Coherence and Polarization in Complex NetworksBabak Ravandi
1and Fatma Mili
2Journal of Computational Social Science, 2019. [journal] [Research Gate]DOI: 10.1007/s42001-019-00036-w
1PhD Candidate in Department of Computer and Information Technology, Purdue University, West Lafayette, Indiana 47906, USA
2Dean and Professor of College of Computing and Informatics, University of North Carolina at Charlotte, Charlotte, USA
In a community, individuals hold opinions and views that are shaped in part by their sources of information and their social network. These opinions and views are rarely uniformly distributed through the possible spectrum. They can exhibit different patterns. We are, in particular, interested in two opposite patterns: polarization, where views are concentrated around extreme positions, and coherence, where views are closer to the center, more moderate positions. We seek to create a model of views evolution and their convergence towards one or another of the patterns. Furthermore, we focus on applying interventions to the structure of networks to demote the polarization issue and influence a network toward convergence of cohered views. Our results show adding links between the weakly-connected nodes reduces polarization, implying the weakly-connected nodes can form bridges between extreme views.
Intervene into the Network Structure to Reduce Polarization
We ask: which missing links are the most influential in decreasing the polarization phenomenon in complex networks? Surprisingly, our results show connecting the weakly-connected nodes is the most effective strategy to decrease polarization.