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arXiv · 2301.13771

The Touché23-ValueEval Dataset for Identifying Human Values behind Arguments

Nailia Mirzakhmedova·Johannes Kiesel·Milad Alshomary·Maximilian Heinrich·Nicolas Handke·Xiaoni Cai·Barriere Valentin·Doratossadat Dastgheib·Omid Ghahroodi·Mohammad Ali Sadraei·Ehsaneddin Asgari·Lea Kawaletz·Henning Wachsmuth·Benno Stein
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Abstract

We present the Touché23-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 Touché23-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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Nailia Mirzakhmedova, Johannes Kiesel, Milad Alshomary, Maximilian Heinrich, Nicolas Handke, Xiaoni Cai, Barriere Valentin, Doratossadat Dastgheib, Omid Ghahroodi, Mohammad Ali Sadraei, Ehsaneddin Asgari, Lea Kawaletz, Henning Wachsmuth, Benno Stein. 2023-01-31. The Touché23-ValueEval Dataset for Identifying Human Values behind Arguments. https://arxiv.org/abs/2301.13771

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