Sentiment analysis on social media using morphological sentence pattern model

Social media became popular than ever as people are willing to share their emotions and opinions or to participate in social networking. Accordingly, the understanding of social media usage became important. The sentiment analysis is emerged as one of useful methods to analyze emotional stats expressed in textual data including social media data. However, this method still presents some limitations, particularly with an accuracy issue. For example, our previous sentiment analysis used a probability model and needed to adopt human-coded train-sets to maintain an acceptable accuracy level (89%). To overcome and improve this weakness, we propose an automated sentiment analysis in this paper by using the morphological sentence pattern model. We found that this new approach presented in this paper allowed us to achieve a higher level of accuracy (91.2%). The movie reviews were used for this analysis from IMDb, Rotten Tomatoes, Metacritic, YouTube and Twitter.