Topic Based Sentiment Analysis Using Deep Learning
This addresses sentiment analysis for social media users, but it is incremental as it builds on existing methods with minor improvements.
The paper tackles sentiment analysis conditioned on topics in Twitter data using a deep learning approach, achieving better performance than state-of-the-art embeddings with standard classifiers.
In this paper , we tackle Sentiment Analysis conditioned on a Topic in Twitter data using Deep Learning . We propose a 2-tier approach : In the first phase we create our own Word Embeddings and see that they do perform better than state-of-the-art embeddings when used with standard classifiers. We then perform inference on these embeddings to learn more about a word with respect to all the topics being considered, and also the top n-influencing words for each topic. In the second phase we use these embeddings to predict the sentiment of the tweet with respect to a given topic, and all other topics under discussion.