Monitoring event-driven dynamics on Twitter: a case study in Belarus

Author:

Rice Natalie M.ORCID,Horne Benjamin D.ORCID,Luther Catherine A.ORCID,Borycz Joshua D.ORCID,Allard Suzie L.ORCID,Ruck Damian J.ORCID,Fitzgerald MichaelORCID,Manaev OlegORCID,Prins Brandon C.ORCID,Taylor MaureenORCID,Bentley R. AlexanderORCID

Abstract

AbstractAnalysts of social media differ in their emphasis on the effects of message content versus social network structure. The balance of these factors may change substantially across time. When a major event occurs, initial independent reactions may give way to more social diffusion of interpretations of the event among different communities, including those committed to disinformation. Here, we explore these dynamics through a case study analysis of the Russian-language Twitter content emerging from Belarus before and after its presidential election of August 9, 2020. From these Russian-language tweets, we extracted a set of topics that characterize the social media data and construct networks to represent the sharing of these topics before and after the election. The case study in Belarus reveals how misinformation can be re-invigorated in discourse through the novelty of a major event. More generally, it suggests how audience networks can shift from influentials dispensing information before an event to a de-centralized sharing of information after it.

Funder

Office of Naval Research

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

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