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        <title>Multi-Target User Stance Discovery on Reddit</title>
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        <name type="personal">
            <namePart type="given">Orphée</namePart>
            <namePart type="family">De Clercq</namePart>
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        <name type="personal">
            <namePart type="given">Valentin</namePart>
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            <namePart type="given">Jeremy</namePart>
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            <namePart type="given">Shabnam</namePart>
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    <abstract>We consider how to credibly and reliably assess the opinions of individuals using their social media posts. To this end, this paper makes three contributions. First, we assemble a workflow and approach to applying modern natural language processing (NLP) methods to multi-target user stance detection in the wild. Second, we establish why the multi-target modeling of user stance is qualitatively more complicated than uni-target user-stance detection. Finally, we validate our method by showing how multi-dimensional measurement of user opinions not only reproduces known opinion polling results, but also enables the study of opinion dynamics at high levels of temporal and semantic resolution.</abstract>
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    <identifier type="doi">10.18653/v1/2024.wassa-1.16</identifier>
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%0 Conference Proceedings
%T Multi-Target User Stance Discovery on Reddit
%A Steel, Benjamin
%A Ruths, Derek
%Y De Clercq, Orphée
%Y Barriere, Valentin
%Y Barnes, Jeremy
%Y Klinger, Roman
%Y Sedoc, João
%Y Tafreshi, Shabnam
%S Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F steel-ruths-2024-multi
%X We consider how to credibly and reliably assess the opinions of individuals using their social media posts. To this end, this paper makes three contributions. First, we assemble a workflow and approach to applying modern natural language processing (NLP) methods to multi-target user stance detection in the wild. Second, we establish why the multi-target modeling of user stance is qualitatively more complicated than uni-target user-stance detection. Finally, we validate our method by showing how multi-dimensional measurement of user opinions not only reproduces known opinion polling results, but also enables the study of opinion dynamics at high levels of temporal and semantic resolution.
%R 10.18653/v1/2024.wassa-1.16
%U https://aclanthology.org/2024.wassa-1.16/
%U https://doi.org/10.18653/v1/2024.wassa-1.16
%P 200-214

Markdown (Informal)

[Multi-Target User Stance Discovery on Reddit](https://aclanthology.org/2024.wassa-1.16/) (Steel & Ruths, WASSA 2024)

• Multi-Target User Stance Discovery on Reddit (Steel & Ruths, WASSA 2024)

ACL

• Benjamin Steel and Derek Ruths. 2024. Multi-Target User Stance Discovery on Reddit. In Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 200–214, Bangkok, Thailand. Association for Computational Linguistics.