Non-Compositionality in Sentiment: New Data and Analyses
October 31, 2023 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
"No code URL or promise found in abstract"
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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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