Why Can't You Convince Me? Modeling Weaknesses in Unpersuasive Arguments

Isaac Persing and Vincent Ng.
Proceedings of the 26th International Joint Conference on Artificial Intelligence, pp. 4082-4088, 2017.

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Abstract

Recent work on argument persuasiveness has focused on determining how persuasive an argument is. Oftentimes, however, it is equally important to understand why an argument is unpersuasive, as it would be difficult for an author to know how to improve her argument's persuasiveness without knowing the errors that made it unpersuasive. Motivated by this practical concern, we (1) annotate a corpus of debate comments with not only their persuasiveness scores but also the errors they contain, (2) propose an approach to persuasiveness scoring and error identification that outperforms competing baselines, and (3) show that the persuasiveness scores computed by our approach can indeed be explained by the errors it identifies.

BibTeX entry

@InProceedings{Persing+Ng:17a,
  author = {Isaac Persing and Vincent Ng},
  title = {Why Can't You Convince Me? Modeling Weaknesses in Unpersuasive Arguments},
  booktitle = {Proceedings of the 26th International Joint Conference on Artificial Intelligence},
  pages = {4082--4088},
  year = 2017}