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Information Epidemics and Collective Action: Network Analysis Perspective

Large groups of people can drastically change their opinion, adopt a completely unexpected trend, come out to protest on a square, adopt a certain ideology, have an amazing time at a party, or start using a certain product on mass scale. While all these social phenomena are diverse, one thing in common is that they involve information dissemination that happens in a synchronized way, evoking a certain response from the population at once.

In this lecture I will demonstrate how epidemic theories from network science can be used to study information contagion and trend/rumor propagation (so-called information cascades). We will use real examples from Facebook and Twitter (Russian protest movements and UK riots), as well as Gephi software to visualise the sample data.

We will learn how successful campaigns (both in marketing, politics, as well as the social sphere) manage to become viral and to provoke a collective action on the side of participants. We will also see how trends, rumours and ideologies are generated and proliferated through social networks. We will also find out how information becomes viral and what one can do in order to increase the message’s contagious potential.

The session will be held by Dmitry Paranyushkin from Berlin-based Nodus Labs, a research organization specialized in using network analysis and complexity science to enhance our understanding of cognitive and social processes.