Sentiment analysis in Twitter - Zhang, Chen (2016)
Nowadays, social media platforms, such as Facebook, Twitter and Instagram, have gained tremendous popularity. These platforms allow people to post real time messages about their opinions on a variety of topics, discuss current issues, complain, and express positive feelings. A rising trend for companies or research institutions to analyse opinions and feelings hidden in messages on social media platform has been seen in recent years. In this thesis, the scope of analysis is narrowed down to opinion mining on the messages on Twitter, the so-called tweets. The specific task is to develop a sentiment analysis system for the three-point scale message polarity subtask of the Twitter sentiment analysis task in Semantic Evaluation Exercises 2016 (SemEval-2016).