Public Riots in Twitter: Domain-Based Event Filtering During Civil Unrest

Arturo Oncevay; Marco Sobrevilla; Hugo Alatrista-Salas; Andrés Melgar

doi:10.1007/978-3-030-55814-7_4

Public Riots in Twitter: Domain-Based Event Filtering During Civil Unrest

Arturo Oncevay
, Marco Sobrevilla
, Hugo Alatrista-Salas
, Andrés Melgar

Universidade de São Paulo
Universidad del Pacífico

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Civil unrest is public manifestations, where people demonstrate their position for different causes. Sometimes, violent events or riots are unleashed in this kind of events, and these can be revealed from tweets posted by involved people. This study describes a methodology to detect riots within the time of a protest to identify potential adverse developments from tweets. Using two own datasets related to a violent and non-violent protest in Peru, we applied temporal clustering to obtain events and identify a tweet headline per cluster. We then extracted relevant terms for the scoring and ranking process using a different domain and contrast corpus built from different sources. Finally, we filtered the relevant events for the violence domain by using a contrast evaluation between the two datasets. The obtained results highlight the adequacy of the proposed approach.

Original language	English
Title of host publication	ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium - International Workshops
Subtitle of host publication	DOING, MADEISD, SKG, BBIGAP, SIMPDA, AIMinScience 2020 and Doctoral Consortium, Proceedings
Editors	Ladjel Bellatreche, Mária Bieliková, Omar Boussaïd, Jérôme Darmont, Barbara Catania, Elena Demidova, Fabien Duchateau, Mark Hall, Tanja Mercun, Maja Žumer, Boris Novikov, Christos Papatheodorou, Thomas Risse, Oscar Romero, Lucile Sautot, Guilaine Talens, Robert Wrembel
Publisher	Springer
Pages	49-59
Number of pages	11
ISBN (Print)	9783030558130
DOIs	https://doi.org/10.1007/978-3-030-55814-7_4
State	Published - 2020
Event	24th East-European Conference on Advances in Databases and Information Systems, ADBIS 2020, the 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, and the 16th Workshop on Business Intelligence and Big Data, EDA 2020 - Lyon, France Duration: 25 Aug 2020 → 27 Aug 2020

Publication series

Name	Communications in Computer and Information Science
Volume	1260 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	24th East-European Conference on Advances in Databases and Information Systems, ADBIS 2020, the 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, and the 16th Workshop on Business Intelligence and Big Data, EDA 2020
Country/Territory	France
City	Lyon
Period	25/08/20 → 27/08/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Keywords

Clustering
Event detection
Riot
Social media analysis

Access to Document

10.1007/978-3-030-55814-7_4

Cite this

Oncevay, A., Sobrevilla, M., Alatrista-Salas, H., & Melgar, A. (2020). Public Riots in Twitter: Domain-Based Event Filtering During Civil Unrest. In L. Bellatreche, M. Bieliková, O. Boussaïd, J. Darmont, B. Catania, E. Demidova, F. Duchateau, M. Hall, T. Mercun, M. Žumer, B. Novikov, C. Papatheodorou, T. Risse, O. Romero, L. Sautot, G. Talens, & R. Wrembel (Eds.), ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium - International Workshops: DOING, MADEISD, SKG, BBIGAP, SIMPDA, AIMinScience 2020 and Doctoral Consortium, Proceedings (pp. 49-59). (Communications in Computer and Information Science; Vol. 1260 CCIS). Springer. https://doi.org/10.1007/978-3-030-55814-7_4

Oncevay, Arturo ; Sobrevilla, Marco ; Alatrista-Salas, Hugo et al. / Public Riots in Twitter : Domain-Based Event Filtering During Civil Unrest. ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium - International Workshops: DOING, MADEISD, SKG, BBIGAP, SIMPDA, AIMinScience 2020 and Doctoral Consortium, Proceedings. editor / Ladjel Bellatreche ; Mária Bieliková ; Omar Boussaïd ; Jérôme Darmont ; Barbara Catania ; Elena Demidova ; Fabien Duchateau ; Mark Hall ; Tanja Mercun ; Maja Žumer ; Boris Novikov ; Christos Papatheodorou ; Thomas Risse ; Oscar Romero ; Lucile Sautot ; Guilaine Talens ; Robert Wrembel. Springer, 2020. pp. 49-59 (Communications in Computer and Information Science).

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title = "Public Riots in Twitter: Domain-Based Event Filtering During Civil Unrest",

abstract = "Civil unrest is public manifestations, where people demonstrate their position for different causes. Sometimes, violent events or riots are unleashed in this kind of events, and these can be revealed from tweets posted by involved people. This study describes a methodology to detect riots within the time of a protest to identify potential adverse developments from tweets. Using two own datasets related to a violent and non-violent protest in Peru, we applied temporal clustering to obtain events and identify a tweet headline per cluster. We then extracted relevant terms for the scoring and ranking process using a different domain and contrast corpus built from different sources. Finally, we filtered the relevant events for the violence domain by using a contrast evaluation between the two datasets. The obtained results highlight the adequacy of the proposed approach.",

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Oncevay, A, Sobrevilla, M, Alatrista-Salas, H & Melgar, A 2020, Public Riots in Twitter: Domain-Based Event Filtering During Civil Unrest. in L Bellatreche, M Bieliková, O Boussaïd, J Darmont, B Catania, E Demidova, F Duchateau, M Hall, T Mercun, M Žumer, B Novikov, C Papatheodorou, T Risse, O Romero, L Sautot, G Talens & R Wrembel (eds), ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium - International Workshops: DOING, MADEISD, SKG, BBIGAP, SIMPDA, AIMinScience 2020 and Doctoral Consortium, Proceedings. Communications in Computer and Information Science, vol. 1260 CCIS, Springer, pp. 49-59, 24th East-European Conference on Advances in Databases and Information Systems, ADBIS 2020, the 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, and the 16th Workshop on Business Intelligence and Big Data, EDA 2020, Lyon, France, 25/08/20. https://doi.org/10.1007/978-3-030-55814-7_4

Public Riots in Twitter: Domain-Based Event Filtering During Civil Unrest. / Oncevay, Arturo; Sobrevilla, Marco; Alatrista-Salas, Hugo et al.
ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium - International Workshops: DOING, MADEISD, SKG, BBIGAP, SIMPDA, AIMinScience 2020 and Doctoral Consortium, Proceedings. ed. / Ladjel Bellatreche; Mária Bieliková; Omar Boussaïd; Jérôme Darmont; Barbara Catania; Elena Demidova; Fabien Duchateau; Mark Hall; Tanja Mercun; Maja Žumer; Boris Novikov; Christos Papatheodorou; Thomas Risse; Oscar Romero; Lucile Sautot; Guilaine Talens; Robert Wrembel. Springer, 2020. p. 49-59 (Communications in Computer and Information Science; Vol. 1260 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Public Riots in Twitter

T2 - 24th East-European Conference on Advances in Databases and Information Systems, ADBIS 2020, the 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, and the 16th Workshop on Business Intelligence and Big Data, EDA 2020

AU - Oncevay, Arturo

AU - Sobrevilla, Marco

AU - Alatrista-Salas, Hugo

AU - Melgar, Andrés

PY - 2020

Y1 - 2020

N2 - Civil unrest is public manifestations, where people demonstrate their position for different causes. Sometimes, violent events or riots are unleashed in this kind of events, and these can be revealed from tweets posted by involved people. This study describes a methodology to detect riots within the time of a protest to identify potential adverse developments from tweets. Using two own datasets related to a violent and non-violent protest in Peru, we applied temporal clustering to obtain events and identify a tweet headline per cluster. We then extracted relevant terms for the scoring and ranking process using a different domain and contrast corpus built from different sources. Finally, we filtered the relevant events for the violence domain by using a contrast evaluation between the two datasets. The obtained results highlight the adequacy of the proposed approach.

AB - Civil unrest is public manifestations, where people demonstrate their position for different causes. Sometimes, violent events or riots are unleashed in this kind of events, and these can be revealed from tweets posted by involved people. This study describes a methodology to detect riots within the time of a protest to identify potential adverse developments from tweets. Using two own datasets related to a violent and non-violent protest in Peru, we applied temporal clustering to obtain events and identify a tweet headline per cluster. We then extracted relevant terms for the scoring and ranking process using a different domain and contrast corpus built from different sources. Finally, we filtered the relevant events for the violence domain by using a contrast evaluation between the two datasets. The obtained results highlight the adequacy of the proposed approach.

KW - Clustering

KW - Event detection

KW - Riot

KW - Social media analysis

UR - https://www.scopus.com/pages/publications/85090094578

U2 - 10.1007/978-3-030-55814-7_4

DO - 10.1007/978-3-030-55814-7_4

M3 - Conference contribution

AN - SCOPUS:85090094578

SN - 9783030558130

T3 - Communications in Computer and Information Science

SP - 49

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BT - ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium - International Workshops

A2 - Bellatreche, Ladjel

A2 - Bieliková, Mária

A2 - Boussaïd, Omar

A2 - Darmont, Jérôme

A2 - Catania, Barbara

A2 - Demidova, Elena

A2 - Duchateau, Fabien

A2 - Hall, Mark

A2 - Mercun, Tanja

A2 - Žumer, Maja

A2 - Novikov, Boris

A2 - Papatheodorou, Christos

A2 - Risse, Thomas

A2 - Romero, Oscar

A2 - Sautot, Lucile

A2 - Talens, Guilaine

A2 - Wrembel, Robert

PB - Springer

Y2 - 25 August 2020 through 27 August 2020

ER -

Oncevay A, Sobrevilla M, Alatrista-Salas H, Melgar A. Public Riots in Twitter: Domain-Based Event Filtering During Civil Unrest. In Bellatreche L, Bieliková M, Boussaïd O, Darmont J, Catania B, Demidova E, Duchateau F, Hall M, Mercun T, Žumer M, Novikov B, Papatheodorou C, Risse T, Romero O, Sautot L, Talens G, Wrembel R, editors, ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium - International Workshops: DOING, MADEISD, SKG, BBIGAP, SIMPDA, AIMinScience 2020 and Doctoral Consortium, Proceedings. Springer. 2020. p. 49-59. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-55814-7_4

Public Riots in Twitter: Domain-Based Event Filtering During Civil Unrest

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this