摘要：Getting a machine to understand the meaning of language is a largely important goal to a wide variety of fields, from advertising to enter- tainment. In this work, we focus on Youtube comments from the top two- hundred trending videos as a source of user text data. Previous Sentiment Analysis Models focus on using hand-labelled data or predetermined lexicon-s.Our goal is to train a model to label comment sentiment with emoticons by training on other user-generated comments containing emoticons. Naive Bayes and Recurrent Neural Network models are both investigated and im- plemented in this study, and the validation accuracies for Naive Bayes model and Recurrent Neural Network model are found to be .548 and .812.
关键词：Sentiment analysis; Emoticons; Natural Language Processing; Machine Learning.
