DocumentCode
3334923
Title
Using SentiWordNet for multilingual sentiment analysis
Author
Denecke, Kerstin
Author_Institution
Res. CenterL3S, Hannover
fYear
2008
fDate
7-12 April 2008
Firstpage
507
Lastpage
512
Abstract
This paper introduces a methodology for determining polarity of text within a multilingual framework. The method leverages on lexical resources for sentiment analysis available in English (SentiWordNet). First, a document in a different language than English is translated into English using standard translation software. Then, the translated document is classified according to its sentiment into one of the classes "positive" and "negative". For sentiment classification, a document is searched for sentiment bearing words like adjectives. By means of SentiWordNet, scores for positivity and negativity are determined for these words. An interpretation of the scores then leads to the document polarity. The method is tested for German movie reviews selected from Amazon and is compared to a statistical polarity classifier based on n-grams. The results show that working with standard technology and existing sentiment analysis approaches is a viable approach to sentiment analysis within a multilingual framework.
Keywords
language translation; natural language processing; word processing; Amazon; English; German movie; SentiWordNet; document polarity; lexical resources; multilingual sentiment analysis; n-grams; sentiment classification; standard translation software; statistical polarity classifier; text polarity; Data mining; Humans; Information services; Machine learning algorithms; Motion pictures; Natural language processing; Natural languages; Software standards; Testing; Web sites;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering Workshop, 2008. ICDEW 2008. IEEE 24th International Conference on
Conference_Location
Cancun
Print_ISBN
978-1-4244-2161-9
Electronic_ISBN
978-1-4244-2162-6
Type
conf
DOI
10.1109/ICDEW.2008.4498370
Filename
4498370
Link To Document