In this paper we tackle an opinion extraction (OE) task, i.e., identifying in a text each expression of subjectivity, the subject expressing it, and its possible target. We especially focus on how lexical resources specifically developed for opinion mining could be used to improve the performance of an opinion extraction system. We report results, complete with statistical significance tests and inter-annotator agreement data, on two manually annotated corpora, one of English and one of Italian texts. We evaluate our results using standard evaluation measures and also using a new evaluation measure we have recently proposed.
Enhancing Opinion Extraction by Automatically Annotated Lexical Resources (Extended Version)
Esuli A;Sebastiani F
2011
Abstract
In this paper we tackle an opinion extraction (OE) task, i.e., identifying in a text each expression of subjectivity, the subject expressing it, and its possible target. We especially focus on how lexical resources specifically developed for opinion mining could be used to improve the performance of an opinion extraction system. We report results, complete with statistical significance tests and inter-annotator agreement data, on two manually annotated corpora, one of English and one of Italian texts. We evaluate our results using standard evaluation measures and also using a new evaluation measure we have recently proposed.File | Dimensione | Formato | |
---|---|---|---|
prod_281510-doc_80076.pdf
solo utenti autorizzati
Descrizione: Enhancing Opinion Extraction by Automatically Annotated Lexical Resources (Extended Version)
Tipologia:
Versione Editoriale (PDF)
Dimensione
207.21 kB
Formato
Adobe PDF
|
207.21 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.