Abstract— Sentiment analysis involves classifying opinions in text into categories like "positive" or "negative". One of approaches used to make sentiment classification is using sentiment lexicon. This paper aims to build a sentiment lexicon which is domain independent. We propose a Machine Learning Based Senti-word Lexicon (MLBSL) based on the Amazon data set which contains reviews from different domains. Our proposed MLBSL yields an improvement over previous published manual and automatic-built lexicons like SentiWordNet. We also provide an improvement in calculation method used in reviews sentiment analysis.

Index Terms—Sentiment Analysis, Sentiment Lexicon, Machine Learning

Cite: Alaa Hamouda, Mahmoud Marei, and Mohamed Rohaim, "Building Machine Learning Based Senti-word Lexicon for Sentiment Analysis," Journal of Advances in Information Technology, Vol. 2, No. 4, pp. 199-203, November, 2011.doi:10.4304/jait.2.4.199-203