| Challenge: | ad hominem attacks are introduced in debates as an easy win, but their impact on argumentation is limited . a machine learning approach to detect the personal attack is insufficient, we show . |
| Approach: | They propose a machine learning approach that detects ad hominem attacks using social media data . they propose TF-IDF approaches that are insufficient to detect the personal attack . |
| Outcome: | The proposed method has a recall of 80% for a social media data source. |
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| Challenge: | Existing research lacks solid empirical investigation of typology of ad hominem arguments and their potential causes. |
| Approach: | They propose to perform several large-scale annotation studies and experiment with various neural architectures to validate hypotheses such as controversy or reasonableness. |
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“Nice Try, Kiddo”: Investigating Ad Hominems in Dialogue Responses (2021.naacl-main)
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| Challenge: | Ad hominem attacks target a person's character instead of the position the person is maintaining. |
| Approach: | They propose to use salient n-gram similarity as a soft constraint to reduce the amount of ad hominems generated in Twitter conversations. |
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Extractive Adversarial Networks: High-Recall Explanations for Identifying Personal Attacks in Social Media Posts (D18-1)
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| Challenge: | Existing work on explaining classifier decisions has not addressed local feature redundancy . a common way to explain why a model classified an example is to extract a sparse subset of features that were responsible for the decision . |
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Argument-based Detection and Classification of Fallacies in Political Debates (2023.emnlp-main)
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| Challenge: | opinion mining is a popular natural language processing technique, but a problem is robustness for user-generated texts . a recent study shows that a model that handles context can extract the opinion target with 90% accuracy . |
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| Challenge: | Political debates are a natural application scenario for Argument Mining. |
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Breaking Down the Invisible Wall of Informal Fallacies in Online Discussions (2021.acl-long)
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Missci: Reconstructing Fallacies in Misrepresented Science (2024.acl-long)
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| Challenge: | False or misleading narratives spread rapidly on social networks, posing challenges for non-experts in discerning credible information. |
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Multimodal Fallacy Classification in Political Debates (2024.eacl-short)
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| Challenge: | Recent advances in NLP suggest that some tasks, such as argument detection and relation classification, are better framed in a multimodal perspective. |
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