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

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

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
EditorsSvetlana S. Bodrunova, Polina Kolozaridi, Leonid Yuldashev, Heiko Niedermayer, Anna Smoliarova, Harry Halpin, Olessia Koltsova, Asbjørn Følstad
PublisherSpringer
Pages61-71
Number of pages11
Volume11551
ISBN (Print)9783030177041
DOIs
StatePublished - 1 Jan 2019
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
CountryRussian Federation
CitySt. Petersburg
Period24/10/1826/10/18

Keywords

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

Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Smoliarova, A. S., Bodrunova, S. S., Yakunin, A. V., Blekanov, I., & Maksimov, A. (2019). Detecting pivotal points in social conflicts via topic modeling of twitter content. In S. S. Bodrunova, P. Kolozaridi, L. Yuldashev, H. Niedermayer, A. Smoliarova, H. Halpin, O. Koltsova, ... A. Følstad (Eds.), Internet Science - INSCI 2018 International Workshops, Revised Selected Papers (Vol. 11551, pp. 61-71). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11551 LNCS). Springer. https://doi.org/10.1007/978-3-030-17705-8_6
Smoliarova, Anna S. ; Bodrunova, Svetlana S. ; Yakunin, Alexandr V. ; Blekanov, Ivan ; Maksimov, Alexey. / Detecting pivotal points in social conflicts via topic modeling of twitter content. Internet Science - INSCI 2018 International Workshops, Revised Selected Papers. editor / Svetlana S. Bodrunova ; Polina Kolozaridi ; Leonid Yuldashev ; Heiko Niedermayer ; Anna Smoliarova ; Harry Halpin ; Olessia Koltsova ; Asbjørn Følstad. Vol. 11551 Springer, 2019. pp. 61-71 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{31d877d6797f4c77a92ba015bb07d711,
title = "Detecting pivotal points in social conflicts via topic modeling of twitter content",
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.",
keywords = "Granger test, Social conflicts, Spillover, Topic modeling, Twitter",
author = "Smoliarova, {Anna S.} and Bodrunova, {Svetlana S.} and Yakunin, {Alexandr V.} and Ivan Blekanov and Alexey Maksimov",
year = "2019",
month = "1",
day = "1",
doi = "10.1007/978-3-030-17705-8_6",
language = "English",
isbn = "9783030177041",
volume = "11551",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "61--71",
editor = "Bodrunova, {Svetlana S.} and Polina Kolozaridi and Leonid Yuldashev and Heiko Niedermayer and Anna Smoliarova and Harry Halpin and Olessia Koltsova and Asbj{\o}rn F{\o}lstad",
booktitle = "Internet Science - INSCI 2018 International Workshops, Revised Selected Papers",
address = "Germany",

}

Smoliarova, AS, Bodrunova, SS, Yakunin, AV, Blekanov, I & Maksimov, A 2019, Detecting pivotal points in social conflicts via topic modeling of twitter content. in SS Bodrunova, P Kolozaridi, L Yuldashev, H Niedermayer, A Smoliarova, H Halpin, O Koltsova & A Følstad (eds), Internet Science - INSCI 2018 International Workshops, Revised Selected Papers. vol. 11551, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11551 LNCS, Springer, pp. 61-71, 5th International Conference on Internet Science, INSCI 2018, St. Petersburg, Russian Federation, 24/10/18. https://doi.org/10.1007/978-3-030-17705-8_6

Detecting pivotal points in social conflicts via topic modeling of twitter content. / Smoliarova, Anna S.; Bodrunova, Svetlana S.; Yakunin, Alexandr V.; Blekanov, Ivan; Maksimov, Alexey.

Internet Science - INSCI 2018 International Workshops, Revised Selected Papers. ed. / Svetlana S. Bodrunova; Polina Kolozaridi; Leonid Yuldashev; Heiko Niedermayer; Anna Smoliarova; Harry Halpin; Olessia Koltsova; Asbjørn Følstad. Vol. 11551 Springer, 2019. p. 61-71 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11551 LNCS).

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

TY - GEN

T1 - Detecting pivotal points in social conflicts via topic modeling of twitter content

AU - Smoliarova, Anna S.

AU - Bodrunova, Svetlana S.

AU - Yakunin, Alexandr V.

AU - Blekanov, Ivan

AU - Maksimov, Alexey

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

KW - Granger test

KW - Social conflicts

KW - Spillover

KW - Topic modeling

KW - Twitter

UR - http://www.scopus.com/inward/record.url?scp=85065339476&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-17705-8_6

DO - 10.1007/978-3-030-17705-8_6

M3 - Conference contribution

SN - 9783030177041

VL - 11551

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 61

EP - 71

BT - Internet Science - INSCI 2018 International Workshops, Revised Selected Papers

A2 - Bodrunova, Svetlana S.

A2 - Kolozaridi, Polina

A2 - Yuldashev, Leonid

A2 - Niedermayer, Heiko

A2 - Smoliarova, Anna

A2 - Halpin, Harry

A2 - Koltsova, Olessia

A2 - Følstad, Asbjørn

PB - Springer

ER -

Smoliarova AS, Bodrunova SS, Yakunin AV, Blekanov I, Maksimov A. Detecting pivotal points in social conflicts via topic modeling of twitter content. In Bodrunova SS, Kolozaridi P, Yuldashev L, Niedermayer H, Smoliarova A, Halpin H, Koltsova O, Følstad A, editors, Internet Science - INSCI 2018 International Workshops, Revised Selected Papers. Vol. 11551. Springer. 2019. p. 61-71. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-17705-8_6