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.