Nikolay Kolyada


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2021

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Beyond Metadata: What Paper Authors Say About Corpora They Use
Nikolay Kolyada | Martin Potthast | Benno Stein
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

2020

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Exploiting Personal Characteristics of Debaters for Predicting Persuasiveness
Khalid Al Khatib | Michael Völske | Shahbaz Syed | Nikolay Kolyada | Benno Stein
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Predicting the persuasiveness of arguments has applications as diverse as writing assistance, essay scoring, and advertising. While clearly relevant to the task, the personal characteristics of an argument’s source and audience have not yet been fully exploited toward automated persuasiveness prediction. In this paper, we model debaters’ prior beliefs, interests, and personality traits based on their previous activity, without dependence on explicit user profiles or questionnaires. Using a dataset of over 60,000 argumentative discussions, comprising more than three million individual posts collected from the subreddit r/ChangeMyView, we demonstrate that our modeling of debater’s characteristics enhances the prediction of argument persuasiveness as well as of debaters’ resistance to persuasion.