Abstract:
Sentiment analysis refers to the inference of people’s views, positions and attitudes in their written or spoken texts. Before the coining of the term, the field was studied under names such as subjectivity, point of view and opinion mining. Nowadays, the field is rapidly evolving due to the rise of new platforms such as blogs, social media and user-generated reviews. Two main research directions can be identified in the literature of sentiment analysis on microblogs. First direction is concerned with finding new methods to run such analysis, such as performing sentiment label propagation on Twitter follower graphs, and employing social relations for user-level sentiment analysis. The second direction is focused on identifying new sets of features to add to the trained model for sentiment identification, such as microblogging features including hashtags, emoticons, the presence of intensifiers such as all-caps and character repetitions etc., and sentiment topic features.
