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

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.