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The Touch\'e23-ValueEval Dataset for Identifying Human Values behind Arguments

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arxiv 2301.13771 v1 pith:T64KYZSN submitted 2023-01-31 cs.CL

Nailia Mirzakhmedova , Johannes Kiesel , Milad Alshomary , Maximilian Heinrich , Nicolas Handke , Xiaoni Cai , Barriere Valentin , Doratossadat Dastgheib
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Omid Ghahroodi Mohammad Ali Sadraei Ehsaneddin Asgari Lea Kawaletz Henning Wachsmuth Benno Stein
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classification cs.CL
keywords argumentsdatasetvaluesbehinde23-valueevalhumantouchidentifying
verification ladder T0 review T1 audit T2 compute T3 formal
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We present the Touch\'e23-ValueEval Dataset for Identifying Human Values behind Arguments. To investigate approaches for the automated detection of human values behind arguments, we collected 9324 arguments from 6 diverse sources, covering religious texts, political discussions, free-text arguments, newspaper editorials, and online democracy platforms. Each argument was annotated by 3 crowdworkers for 54 values. The Touch\'e23-ValueEval dataset extends the Webis-ArgValues-22. In comparison to the previous dataset, the effectiveness of a 1-Baseline decreases, but that of an out-of-the-box BERT model increases. Therefore, though the classification difficulty increased as per the label distribution, the larger dataset allows for training better models.

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