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        <title>Supervised Event Coding from Text Written in Arabic: Introducing Hadath</title>
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        <namePart type="given">Javier</namePart>
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        <namePart type="given">Alejandro</namePart>
        <namePart type="family">Reyes</namePart>
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    <name type="personal">
        <namePart type="given">Alejandro</namePart>
        <namePart type="family">Beltrán</namePart>
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    <name type="personal">
        <namePart type="given">Atal</namePart>
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            <title>Proceedings of the Workshop on Automated Extraction of Socio-political Events from News 2020</title>
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        <name type="personal">
            <namePart type="given">Ali</namePart>
            <namePart type="family">Hürriyetoğlu</namePart>
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        <name type="personal">
            <namePart type="given">Erdem</namePart>
            <namePart type="family">Yörük</namePart>
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        <name type="personal">
            <namePart type="given">Vanni</namePart>
            <namePart type="family">Zavarella</namePart>
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    <abstract>This article introduces Hadath, a supervised protocol for coding event data from text written in Arabic. Hadath contributes to recent efforts in advancing multi-language event coding using computer-based solutions. In this application, we focus on extracting event data about the conflict in Afghanistan from 2008 to 2018 using Arabic information sources. The implementation relies first on a Machine Learning algorithm to classify news stories relevant to the Afghan conflict. Then, using Hadath, we implement the Natural Language Processing component for event coding from Arabic script. The output database contains daily geo-referenced information at the district level on who did what to whom, when and where in the Afghan conflict. The data helps to identify trends in the dynamics of violence, the provision of governance, and traditional conflict resolution in Afghanistan for different actors over time and across space.</abstract>
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%0 Conference Proceedings
%T Supervised Event Coding from Text Written in Arabic: Introducing Hadath
%A Osorio, Javier
%A Reyes, Alejandro
%A Beltrán, Alejandro
%A Ahmadzai, Atal
%Y Hürriyetoğlu, Ali
%Y Yörük, Erdem
%Y Zavarella, Vanni
%Y Tanev, Hristo
%S Proceedings of the Workshop on Automated Extraction of Socio-political Events from News 2020
%D 2020
%8 May
%I European Language Resources Association (ELRA)
%C Marseille, France
%@ 979-10-95546-50-4
%G English
%F osorio-etal-2020-supervised
%X This article introduces Hadath, a supervised protocol for coding event data from text written in Arabic. Hadath contributes to recent efforts in advancing multi-language event coding using computer-based solutions. In this application, we focus on extracting event data about the conflict in Afghanistan from 2008 to 2018 using Arabic information sources. The implementation relies first on a Machine Learning algorithm to classify news stories relevant to the Afghan conflict. Then, using Hadath, we implement the Natural Language Processing component for event coding from Arabic script. The output database contains daily geo-referenced information at the district level on who did what to whom, when and where in the Afghan conflict. The data helps to identify trends in the dynamics of violence, the provision of governance, and traditional conflict resolution in Afghanistan for different actors over time and across space.
%U https://aclanthology.org/2020.aespen-1.9
%P 49-56

Markdown (Informal)

[Supervised Event Coding from Text Written in Arabic: Introducing Hadath](https://aclanthology.org/2020.aespen-1.9) (Osorio et al., AESPEN 2020)

• Supervised Event Coding from Text Written in Arabic: Introducing Hadath (Osorio et al., AESPEN 2020)

ACL

• Javier Osorio, Alejandro Reyes, Alejandro Beltrán, and Atal Ahmadzai. 2020. Supervised Event Coding from Text Written in Arabic: Introducing Hadath. In Proceedings of the Workshop on Automated Extraction of Socio-political Events from News 2020, pages 49–56, Marseille, France. European Language Resources Association (ELRA).