Further Experiments in Sentiment Analysis of French Movie Reviews

Autor:	Hatem Ghorbel, David Jacot
Rok vydání:	2011
Předmět:	business.industry Computer science Polarity (physics) Supervised learning Sentiment analysis computer.software_genre Field (computer science) Focus (linguistics) Negation Bag-of-words model Chunking (psychology) Artificial intelligence business computer Natural language processing
Zdroj:	Advances in Intelligent and Soft Computing ISBN: 9783642180286 AWIC
DOI:	10.1007/978-3-642-18029-3_3
Popis:	In sentiment analysis of reviews we focus on classifying the polarity (positive, negative) of conveyed opinions from the perspective of textual evidence. Most of the work in the field has been intensively applied on the English language and only few experiments have explored other languages. In this paper, we present a supervised classification of French movie reviews where sentiment analysis is based on some shallow linguistic features such as POS tagging, chunking and simple negation forms. In order to improve classification, we extracted word semantic orientation from the lexical resource SentiWordNet. Since SentiWordNet is an English resource, we apply a word-translation from French to English before polarity extraction. Our approach is evaluated on French movie reviews, obtained results showed that shallow linguistic features has significantly improved the classification performance with respect to the bag of words baseline.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7d4ba8148ae45b77cb31011a988a0d44 https://doi.org/10.1007/978-3-642-18029-3_3 Zobrazit plný text záznamu