Identifying Themes in Social Media and Detecting Sentiments
Recently, a huge wave of social media has generated significant impact in people's perceptions about technological domains. They are captured in several blogs/forums, where the themes relate to products of several companies. One of the companies can be interested to track them as resources for customer perceptions and detect user sentiments. The keyword-based approaches for identifying such themes fail to give satisfactory level of accuracy. Here, the paper addresses the above problems using statistical text-mining of blog entries. The crux of the analysis lies in mining quantitative information from textual entries. Once the relevant blog entries for the company/its competitors are filtered out, the theme identification is performed using a highly accurate novel technique termed as 'Best Separators Algorithm'.