A balanced sentiment analysis approach with stemming porter for neutralized emotion weightage

Abstract: The application of sentiment analysis, also known as opinion mining, is more difficult in Chinese than in Indo-European languages, due to the compounding nature of Chinese words and phrases, and relatively lack of reliable resources in Chinese. This study used seed words, Chinese morphemes, which are mono-syllabic characters that function as individual words or be combined to create Chinese word and phrases, to classify movie reviews found on Yahoo. We use a lexicon based approach for discovering sentiments.Our lexicon is built from the Serendio taxonomy.The Serendio taxonomy consists of positive, negative, negation, stop words and phrases. A typical tweet contains word variations,emoticons, hashtags etc. We use preprocessing steps such as stemming, emoticon detection and normalization, exaggerated word shortening and hashtag detection. After the preprocessing, the lexicon-based system classifiesthe tweets as positive or negative based on the contextual sentiment orientation of the words.

Keywords: NLP, Artificial Intelligence (AI), Sentiment Analysis, Serendio taxonomy.