Sentiment Analysis of Social Messages Using Supervised Learning Approach
Abstract
Recently new forms of communication, such as microblogging and text messaging have emerged and finds everywhere. While there is no limit to the range of information conveyed by tweets and texts, often these short messages are used to share opinions,thought and sentiments that people have about what is going on in the world around them. The project proposes this task and the development and analysis of a twitter sentiment corpus to promote research that will lead to a better understanding of how sentiment is conveyed in tweets and texts. For this development Twitter API is used to collect corpus of text posts and forming a data set for the module. There will be two sub-tasks: an expression-level task and a message-level task; participants may choose to participate in either or both tasks.
References
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