Mining Blogger Sentiments Using an Improved Lexicon-based Approach
نویسنده
چکیده
This paper presents a sentiment lexicon-based algorithmic approach to mine sentiments in blog posts. The experimental system is designed to use a publicly available sentiment lexicon, the SentiWordNet, and identify opinion polarities from blog texts. Two schemes of based on SentiWordNet, namely SWN (AAC) and SWN (AAAVC) are designed and evaluated on two labeled blog datasets. The schemes use adverb+adjective and adverb+verb combines for selecting opinion holder features. The accuracy of the two implementations is evaluated by computing standard performance measures on labeled datasets. The proposed method obtains good results and shows the suitability of feature selection schemes and the algorithmic design.
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