Protest Event Detection: When Task-Specific Models Outperform an Event-Driven Method

Angelo Basile, Tommaso Caselli*

*Corresponding author for this work

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

    3 Citations (Scopus)


    2019 has been characterized by worldwide waves of protests. Each country’s protests is different but there appear to be common factors. In this paper we present two approaches for identifying protest events in news in English. Our goal is to provide political science and discourse analysis scholars with tools that may facilitate the understanding of this on-going phenomenon. We test our approaches against the ProtestNews Lab 2019 benchmark that challenges systems to perform unsupervised domain adaptation on protest events on three sub-tasks: document classification, sentence classification, and event extraction. Results indicate that developing dedicated architectures and models for each task outperforms simpler solutions based on the propagation of labels from lexical items to documents. Furthermore, we complete the description of our systems with a detailed data analysis to shed light on the limits of the methods.

    Original languageEnglish
    Title of host publicationExperimental IR Meets Multilinguality, Multimodality, and Interaction - 11th International Conference of the CLEF Association, CLEF 2020, Proceedings
    EditorsAvi Arampatzis, Evangelos Kanoulas, Theodora Tsikrika, Stefanos Vrochidis, Hideo Joho, Christina Lioma, Carsten Eickhoff, Aurélie Névéol, Aurélie Névéol, Linda Cappellato, Nicola Ferro
    PublisherSpringer Science and Business Media Deutschland GmbH
    Number of pages15
    ISBN (Print)9783030582180
    Publication statusPublished - 2020
    Event11th Conference and Labs of the Evaluation Forum, CLEF 2020 - Thessaloniki, Greece
    Duration: 22-Sept-202025-Sept-2020

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume12260 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference11th Conference and Labs of the Evaluation Forum, CLEF 2020


    • Document classification
    • Event extraction
    • Protest events
    • Sentence classification

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