Analysis of Classification Techniques for Mining Reviews Using Lexicon and WordNet Using R

with the exponential growth of social media i.e. blogs and social networks, organizations and individual persons are increasingly using the number of reviews of these media for decision making about a product or service. Opinion mining detects whether the emotions of an opinion expressed by a user on Web platforms in natural language, is positive or negative. This paper presents extensive experiments to study the effectiveness of the classification of English type opinions in three categories: positive, negative and none. For this study, technological products corpora have been used. Furthermore, we have conducted a comparative assessment of the analysis of two classification techniques: J48 and C50 using the effect of both Opinion Lexicon and WordNet. Experimental results shows that the WordNet based sentiment classification perform well over Opinion Lexicon based classification. The proposed technique can also be used with any other language. The whole work is implemented using ‘R’ language.