Extracting word-of-mouth sentiments via sentiwordnet for document quality classification

Chihli Hung, Chih Fong Tsai, Hsinyi Huang

Research output: Contribution to journalReview articlepeer-review

11 Scopus citations


Word of mouth (WOM) with good information quality has a significant influence on consumer behaviors. A WOM document containing an evident sentimental orientation is one of the most important features of information quality. Although a high coverage sentimental WordNet lexicon, i.e. SentiWordNet, has been developed, its performance when applying it to WOM quality classification for WOM is not yet known. This research uses SentiWordNet for tagging sentimental orientations and classifying documents into different qualitative categories. Results from our experiments demonstrate that this proposed approach has a strong potential for use in WOM quality classification. A review outlining patents relevant to SentiWordNet is provided.

Original languageEnglish
Pages (from-to)145-152
Number of pages8
JournalRecent Patents on Computer Science
Issue number2
StatePublished - Aug 2012


  • Document quality classification
  • Information quality
  • Opinion mining
  • Sentiment analysis
  • Sentiwordnet
  • Word of mouth classification
  • Wordnet


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