Indexed on: 13 May '16Published on: 04 Mar '16Published in: International Journal of Cloud Computing
Opinion mining started getting more traction due to the increasing popularity of Twitter and similar social network platforms that are producing fast and real-;time responses to social events. It is a very challenging area since it is difficult, if not impossible, to identify general public sentiment towards events, entities, etc., using opinion mining techniques over huge numbers of tweets and messages automatically. In this study we present our opinion mining techniques on tweet data with early results. We apply sentiment scoring and clustering algorithms using Hadoop ecosystem for parallel processing. We classify tweets by tagging them as positive, negative, and neutral as a result.