Polarized Communities in Online Social Networks
Analyses, algorithms, applications
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Increasingly, people around the globe use Social Media (SM) - e.g. Facebook, Twitter, Tumblr, Flickr, Youtube - to publish multimedia content (posting), to share it (retweeting, reblogging or sharing), to reinforce it or not (liking, disliking) and to discuss (through messages and comments) in order to be in contact with other users and to get informed about topics of interest. The world population is = 7.4 billion people, among them = 2.3 billion (31%) are active social media users (Global Web Index data, Jan 2016). Online Social Networks (OSNs), then, provide a space for user aggregation in ...
Increasingly, people around the globe use Social Media (SM) - e.g. Facebook, Twitter, Tumblr, Flickr, Youtube - to publish multimedia content (posting), to share it (retweeting, reblogging or sharing), to reinforce it or not (liking, disliking) and to discuss (through messages and comments) in order to be in contact with other users and to get informed about topics of interest. The world population is = 7.4 billion people, among them = 2.3 billion (31%) are active social media users (Global Web Index data, Jan 2016). Online Social Networks (OSNs), then, provide a space for user aggregation in groups, expressing opinions, accessing information, contributing to public debates, and participating in the formation of belief systems. In this context, communities are built around different topics of interaction and polarized sub-groups often emerge by clustering different opinions and points of view. Such polarized sub-groups can be tracked and monitored over time in an automatic way and the analysis of their interactions is interesting to shed light on the human social behavior.
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