On Sentiment Polarity Assignment In The Wordnet Using Loopy Belief Propagation

Sentiment analysis is a very active and nowadays highly addressed research area. One of the problem in sentiment analysis is text classification in terms of its attitude, especially in reviews or comments from social media. In general, this problem can be solved by two different approaches: machine learning methods and based on lexicons. Methods based on lexicons require properly prepared lexicons which usually are obtained manually from experts and it costs a lot in terms of time and resources. This paper aims at automatic lexicon creation for sentiment analysis. There are proposed the methods based on Loopy Belief Propagation that starting from small set of seed words with a priori known sentiment value propagates the sentiment to whole Wordnet.