Sentiment Analysis for Kannada using mobile product reviews: A case study

Sentiment Analysis (SA) is a very popular research area in the field of text mining as its computational capabilities have found a lot of research applications. Sentiment Prediction,Subjectivity Detection,Text summarization,Sentiment Summarization for Opinions etc. are some example applications. There are many research studies in the area of SA in different languages. However, Kannada SA has not been explored extensively and in particular, for the analysis of product reviews. In this paper, a case study of Kannada SA for mobile product reviews is proposed as there are many user generated Kannada product reviews available online. In this approach a lexicon based method for aspect extraction has been developed. Furthermore, the Naive Bayes classification model is applied to analyze the polarity of the sentiment due to its computational simplicity and stochastic robustness. This is the first attempt in Kannada to the best of author´s knowledge. Therefore, a customized corpus has been developed. The weekly reviews from the column `Gadget Loka´ by U.B Pavanaja are considered to develop this corpus. The source for this is the famous Kannada news paper `Prajavani´. The preliminary results indicate this approach is an efficient technique for Kannada SA.