Pragmatic Perspective on Assessing Implicit Meaning Interpretation in Sentiment Analysis Models

Rashid Mustafin

Keywords: sentiment analysis, pragmatics, implicatures, transformers

TL;DR: Transformer sentiment analysis models base their decisions on (sometimes erroneous) formal markers of sentiment regardless of the pragmatic interpretation.

Abstract: Drawing on pragmatic theories of implicature by Grice (1975) and Levinson (1983), according to which speakers often convey more than it is explicitly said, the paper argues that interpreting texts with implicit meaning correctly is essential for precise sentiment analysis. To illustrate the challenges in computational interpretation of implicatures, the study introduces a series of illustrative micro-experiments with the use of four transformer models fine-tuned for sentiment analysis. In these micro-experiments, the models classified sentences specifically designed to expose difficulties in handling implicit meaning. The study demonstrates that contrasting qualitative pragmatic analysis with the models' tendency to focus on formal linguistic markers can reveal the limitations of supervised machine learning methods in detecting implicit sentiments.

Archival Status: Archival

Paper Length: Short Paper (up to 4 pages of content)

Submission Number: 232