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Databases and Information Systems in the AI Era: Contributions from ADBIS, TPDL and EDA 2020 Workshops and Doctoral Consortium Read chapter Read first chapter

2020 | OriginalPaper | Chapter

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

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

Published in: ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium

Publisher: Springer International Publishing

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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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Footnotes
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Metadata
Title
Public Riots in Twitter: Domain-Based Event Filtering During Civil Unrest
Authors
Arturo Oncevay
Marco Sobrevilla
Hugo Alatrista-Salas
Andrés Melgar
Copyright Year
2020
Book
ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium

Print ISBN: 978-3-030-55813-0

Electronic ISBN: 978-3-030-55814-7

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-55814-7_4

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