Non-Compositionality in Sentiment: New Data and Analyses

October 31, 2023 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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Authors Verna Dankers, Christopher G. Lucas arXiv ID 2310.20656 Category cs.CL: Computation & Language Citations 2 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 5 months ago
Abstract
When natural language phrases are combined, their meaning is often more than the sum of their parts. In the context of NLP tasks such as sentiment analysis, where the meaning of a phrase is its sentiment, that still applies. Many NLP studies on sentiment analysis, however, focus on the fact that sentiment computations are largely compositional. We, instead, set out to obtain non-compositionality ratings for phrases with respect to their sentiment. Our contributions are as follows: a) a methodology for obtaining those non-compositionality ratings, b) a resource of ratings for 259 phrases -- NonCompSST -- along with an analysis of that resource, and c) an evaluation of computational models for sentiment analysis using this new resource.
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