Lexicon-based Sentiment Analysis relies on sentiment dictionaries which are used to assign a sentiment polarity to the words of an input text. The overall sentiment of the text is then computed by means of a combining function, such as the word count, sum or average. In this short contribution we describe a detailed set of linguistic rules that allow to understand the text fragments which are semantically linked to a given concept of interest in a text. These heuristics have been designed in the spirit of the recent Interpretable AI trend, since they allow to understand the origin of sentiment for a specific term, providing more transparency and interpretation of the resulting analysis, and enabling the development of advanced and novel lexicon-based Sentiment Analysis approaches, which is the object of our currently on-going work.
CONSOLI Sergio;
BARBAGLIA Luca;
MANZAN Sebastiano;
2021-08-02
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JRC124179
1613-0073 (online),
http://ceur-ws.org/Vol-2918/paper7.pdf,
https://publications.jrc.ec.europa.eu/repository/handle/JRC124179,
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