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 opinions with preserving a substantial overall polarity prediction.