N-Gram Based Sentiment Mining for Bangla Text Using Support Vector Machine

Opinion Mining is a valuable knowledge resource to understand the collective opinions and to take better decisions. It is a Natural Language Processing (NLP) task that decides whether a text expresses positive or negative sentiment. Web contents are increasing rapidly and providing a huge number of information. It is an important research issue to analyze and organize these enormous information for better knowledge extraction. In this paper, we emphasis on opinion mining for Bangla text using web based diverse data. We apply both Linear and Nonlinear Support Vector Machine as machine learning technique and N -gram method to classify Bangla documents collected from social media sites. Most of works in this arena take a single word as a vector. Instead of thinking a single word as a vector, we used one vector containing more than one words using N-gram. N-grams of texts are extensively used in text mining and natural language processing tasks. We found better results using N-grams for different values of n.