RESEARCH OF CONSTRUCTING THE SENTIMENT CLASSIFICATION PROCESS ON VIETNAMESE TEXTS

Abstract

Text classification is the process of analyzing text content and then giving decision whether this text  could belong to one group, many groups or it does not belong to the text group which is defined before. Sentiment classification is a special kind of text classification in which a document is classified to predict automatically sentiment polarity (positive or negative). In all over the world, there have been many effective researches on this problem, especially on texts in English.  However, there have been few researches on Vietnamese texts. Moreover,  these  researching  results  and  applications  are  still  limited  partly  due  to  the  typical characteristics  of  Vietnamese  language  in  term  of  words  and  sentences  and  there  are  many  words with many meanings in many different contexts. In this research, the author constructs a model to serve the process of sentiment classification on Vietnamese texts and suggests techniques feature selection for that process.