Detecting pivotal points in social conflicts via topic modeling of twitter content

Anna S. Smoliarova*, Svetlana S. Bodrunova, Alexandr V. Yakunin, Ivan Blekanov, Alexey Maksimov

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

The linkages between intensity and topicality of online discussions, on one hand, and those of offline on-street political activity, on the other hand, have recently become a subject of studies around the world. But the results of quantitative assessment of causal relations between onsite and online activities of citizens are contradictory. In our research, we use conflicts with violent trig-gers and the subsequent lines of events that include street rallies, political manifestations, and/or peaceful mourning, as well as public political talk, to trace the pivotal points in the conflict via measuring Twitter content. We show that in some cases Granger test does not work well, like in the case of Cologne mass harassment, for detecting the causality between online and onsite activities. In order to suggest a way to qualitatively assess the linkages between online and offline activities of users, we deploy topic modeling and further qualitative assessment of the changes in the topicality to link the topic saliency to the time of offline events. We detect several periods with varying topicality and link them to what was going on in the offline conflict.

Original languageEnglish
Title of host publicationInternet Science - INSCI 2018 International Workshops, Revised Selected Papers
EditorsAsbjørn Følstad, Svetlana S. Bodrunova, Anna Smoliarova, Olessia Koltsova, Heiko Niedermayer, Polina Kolozaridi, Leonid Yuldashev, Harry Halpin
PublisherSpringer Verlag
Pages61-71
Number of pages11
ISBN (Print)9783030177041
DOIs
StatePublished - 2019
Externally publishedYes
Event5th International Conference on Internet Science, INSCI 2018 - St. Petersburg, Russian Federation
Duration: 24 Oct 201826 Oct 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11551 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Internet Science, INSCI 2018
Country/TerritoryRussian Federation
CitySt. Petersburg
Period24/10/1826/10/18

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2019.

Keywords

  • Granger test
  • Social conflicts
  • Spillover
  • Topic modeling
  • Twitter

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