Enrichissement d'un lexique de termes subjectifs à partir de tests sémantiques

Matthieu Vernier (1) , Laura Monceaux (1)

1 LINA - Laboratoire d'Informatique de Nantes Atlantique

Recent considerations in opinion mining, oriented by real applicative tasks, require creating lexical and semantic resources quantitatively and qualitatively rich. In this context, we present a method to automatically enhance a lexicon of subjective terms. he method relies on the indexing of documents by a search engine and large number of requests automatically sent. The construction of these requests, linguistically motivated, can infer the value of semantics and axiological aspect of a large number of adjectives, nouns and noun phrases, verbs and verbal phrases of French. We then evaluate the lexicon enhancement by testing the detection of local evaluation in a corpus of 5 000 blogs notes and comments.

Mots clés: Machine learning; Opinion mining; Subjectivity; Lexical and semantic resource; Machine learning.

Domaines: Traitement du texte et du document

Matthieu Vernier, Laura Monceaux. Enrichissement d'un lexique de termes subjectifs à partir de tests sémantiques. Revue TAL : traitement automatique des langues, 2010, 51 (1), pp.125--149. ⟨hal-00472165⟩