Extracting Word-of-Mouth Sentiments via SentiWordNet for Document Quality Classification

Title:Extracting Word-of-Mouth Sentiments via SentiWordNet for Document Quality Classification

Volume: 5 Issue: 2

Author(s): Chihli Hung, Chih-Fong Tsai and Hsinyi Huang

Affiliation:

Keywords: Document quality classification, information quality, opinion mining, sentiment analysis, SentiWordNet, word of mouth classification, WordNet, WOM Collecting, Document Preprocessing, Quality Classification

Abstract: 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.

Cite this article as:

Hung Chihli, Tsai Chih-Fong and Huang Hsinyi, Extracting Word-of-Mouth Sentiments via SentiWordNet for Document Quality Classification, Recent Patents on Computer Science 2012; 5 (2) . https://dx.doi.org/10.2174/2213275911205020145