Year: 2017
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: S., Sharath T., Tandon, Shubhangi
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4298223959