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On Classifying whether Two Texts are on the Same Side of an Argument ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.795/ Abstract: To ease the difficulty of argument stance classification, the task of same side stance classification (S3C) has been proposed. In contrast to actual stance classification, which requires a substantial amount of domain knowledge to identify whether an argument is in favor or against a certain issue, it is argued that, for S3C, only argument similarity within stances needs to be learned to successfully solve the task. We evaluate several transformer-based approaches on the dataset of the recent S3C shared task, followed by an in-depth evaluation and error analysis of our model and the task's hypothesis. We show that, although we achieve state-of-the-art results, our model fails to generalize both within as well as across topics and domains when adjusting the sampling strategy of the training and test set to a more adversarial scenario. Our evaluation shows that current state-of-the-art approaches cannot determine same side stance by ...
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Keyword:
Language Models; Natural Language Processing; Semantic Evaluation; Sociolinguistics
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URL: https://underline.io/lecture/37386-on-classifying-whether-two-texts-are-on-the-same-side-of-an-argument
https://dx.doi.org/10.48448/wmx4-0145
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AWESSOME : An unsupervised sentiment intensity scoring framework using neural word embeddings
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Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
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Webis Argument Quality Corpus 2020 (Webis-ArgQuality-20) ...
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Webis Argument Quality Corpus 2020 (Webis-ArgQuality-20) ...
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Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection
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Overview of PAN 2019: Bots and Gender Profiling, Celebrity Profiling, Cross-domain Authorship Attribution and Style Change Detection
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Overview of PAN 2018. Author identification, author profiling, and author obfuscation
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CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
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Overview of PAN'17: Author Identification, Author Profiling, and Author Obfuscation
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