Twitter Sentiment Analysis with Recursive Neural Networks

In this paper, we explore the application of Recursive Neural Networks on the sentiment analysis task with tweets. Tweets, being a form of communication that has been largely infused with symbols and short-hands, are especially challenging as a sentiment analysis task. In this project, we experiment with different genres of neural net and analyze how models suit the data set in which the nature of the data and model structures come to play. The neural net structures we experimented include one-hidden-layer Recursive Neural Net (RNN), two-hidden-layer RNN and Recursive Neural Tensor Net (RNTN). Different data filtering layers, such as ReLU, tanh, and drop-out also yields many insights while different combination of them might affect the performance in different ways.