<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="olsen-etal-2024-socio">
    <titleInfo>
        <title>Socio-political Events of Conflict and Unrest: A Survey of Available Datasets</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Helene</namePart>
        <namePart type="family">Olsen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Étienne</namePart>
        <namePart type="family">Simon</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Erik</namePart>
        <namePart type="family">Velldal</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Lilja</namePart>
        <namePart type="family">Øvrelid</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-03</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Ali</namePart>
            <namePart type="family">Hürriyetoğlu</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Hristo</namePart>
            <namePart type="family">Tanev</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Surendrabikram</namePart>
            <namePart type="family">Thapa</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Gökçe</namePart>
            <namePart type="family">Uludoğan</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">St. Julians, Malta</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>There is a large and growing body of literature on datasets created to facilitate the study of socio-political events of conflict and unrest. However, the datasets, and the approaches taken to create them, vary a lot depending on the type of research they are intended to support. For example, while scholars from natural language processing (NLP) tend to focus on annotating specific spans of text indicating various components of an event, scholars from the disciplines of political science and conflict studies tend to focus on creating databases that code an abstract but structured representation of the event, less tied to a specific source text.The survey presented in this paper aims to map out the current landscape of available event datasets within the domain of social and political conflict and unrest – both from the NLP and political science communities – offering a unified view of the work done across different disciplines.</abstract>
    <identifier type="citekey">olsen-etal-2024-socio</identifier>
    <location>
        <url>https://aclanthology.org/2024.case-1.5</url>
    </location>
    <part>
        <date>2024-03</date>
        <extent unit="page">
            <start>40</start>
            <end>53</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Socio-political Events of Conflict and Unrest: A Survey of Available Datasets
%A Olsen, Helene
%A Simon, Étienne
%A Velldal, Erik
%A Øvrelid, Lilja
%Y Hürriyetoğlu, Ali
%Y Tanev, Hristo
%Y Thapa, Surendrabikram
%Y Uludoğan, Gökçe
%S Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024)
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julians, Malta
%F olsen-etal-2024-socio
%X There is a large and growing body of literature on datasets created to facilitate the study of socio-political events of conflict and unrest. However, the datasets, and the approaches taken to create them, vary a lot depending on the type of research they are intended to support. For example, while scholars from natural language processing (NLP) tend to focus on annotating specific spans of text indicating various components of an event, scholars from the disciplines of political science and conflict studies tend to focus on creating databases that code an abstract but structured representation of the event, less tied to a specific source text.The survey presented in this paper aims to map out the current landscape of available event datasets within the domain of social and political conflict and unrest – both from the NLP and political science communities – offering a unified view of the work done across different disciplines.
%U https://aclanthology.org/2024.case-1.5
%P 40-53

Markdown (Informal)

[Socio-political Events of Conflict and Unrest: A Survey of Available Datasets](https://aclanthology.org/2024.case-1.5) (Olsen et al., CASE-WS 2024)

• Socio-political Events of Conflict and Unrest: A Survey of Available Datasets (Olsen et al., CASE-WS 2024)

ACL

• Helene Olsen, Étienne Simon, Erik Velldal, and Lilja Øvrelid. 2024. Socio-political Events of Conflict and Unrest: A Survey of Available Datasets. In Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024), pages 40–53, St. Julians, Malta. Association for Computational Linguistics.