Twitter Sentiment Analysis System
Computation and Language
2018-07-23 v1 Machine Learning
Machine Learning
Abstract
Social media is increasingly used by humans to express their feelings and opinions in the form of short text messages. Detecting sentiments in the text has a wide range of applications including identifying anxiety or depression of individuals and measuring well-being or mood of a community. Sentiments can be expressed in many ways that can be seen such as facial expression and gestures, speech and by written text. Sentiment Analysis in text documents is essentially a content-based classification problem involving concepts from the domains of Natural Language Processing as well as Machine Learning. In this paper, sentiment recognition based on textual data and the techniques used in sentiment analysis are discussed.
Cite
@article{arxiv.1807.07752,
title = {Twitter Sentiment Analysis System},
author = {Shaunak Joshi and Deepali Deshpande},
journal= {arXiv preprint arXiv:1807.07752},
year = {2018}
}
Comments
5 pages