Learning Subjectivity Phrases missing from Resources through a Large Set of Semantic Tests - Archive ouverte HAL
Communication Dans Un Congrès Année : 2010

Learning Subjectivity Phrases missing from Resources through a Large Set of Semantic Tests

Résumé

In recent years, blogs and social networks have particularly boosted interests for opinion mining research. In order to satisfy real-scale applicative needs, a main task is to create or to enhance lexical and semantic resources on evaluative language. Classical resources of the area are mostly built for english, they contain simple opinion word markers and are far to cover the lexical richness of this linguistic phenomenon. We propose a new method, applied on french, to enhance automatically an opinion word lexicon. This learning method relies on linguistic uses of internet users and on semantic tests to infer the degree of subjectivity of many new adjectives, nouns, verbs, noun phrases, verbal phrases which are usually forgotten by other resources.
Fichier principal
Vignette du fichier
LREC10-Vernier-final.pdf (109.16 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00472168 , version 1 (09-04-2010)

Identifiants

  • HAL Id : hal-00472168 , version 1

Citer

Matthieu Vernier, Laura Monceaux, Béatrice Daille. Learning Subjectivity Phrases missing from Resources through a Large Set of Semantic Tests. The 7th International Conference on Language Resources and Evaluation (LREC'10), May 2010, La Valette, Malta. pp.1335--1341. ⟨hal-00472168⟩
135 Consultations
195 Téléchargements

Partager

More