The neutrality detection in Sentiment Analysis (SA) still constitutes an unsolved and debated issue. This work proposes an empirical method based on the quartiles of the polarity distribution for a lexicon-based SA approach. Our experiments are based on the Italian linguistic resource MAL (Morphologically-inflected Affective Lexicon) and applied to two annotated corpora. The findings provided a better detection of the neutral expressions with preserving a substantial overall polarity prediction.

Neutral Score Detection in Lexicon-based Sentiment Analysis: the Quartile-based Approach

Basile V.
Membro del Collaboration Group
;
Bosco C.
2024-01-01

Abstract

The neutrality detection in Sentiment Analysis (SA) still constitutes an unsolved and debated issue. This work proposes an empirical method based on the quartiles of the polarity distribution for a lexicon-based SA approach. Our experiments are based on the Italian linguistic resource MAL (Morphologically-inflected Affective Lexicon) and applied to two annotated corpora. The findings provided a better detection of the neutral expressions with preserving a substantial overall polarity prediction.
2024
10th Italian Conference on Computational Linguistics, CLiC-it 2024
ita
2024
CEUR Workshop Proceedings
CEUR-WS
3878
976
982
Lexicon; Neutrality; Optimization; Sentiment Analysis
Vassallo M.; Gabrieli G.; Basile V.; Bosco C.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2077391
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