Comparison of algorithms for Twitter sentiment analysis
Access full-text files
Date
2017-05
Authors
Whipple, Adam Lane
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Sentiment Analysis has gained attention in recent years owing to the massive increase in personal statements made at the individual level, spread across vast geographic and demographic ranges. That data has become vastly more accessible as micro-blog sites such as Twitter and Facebook have released public, free interfaces. This research seeks to understand the processes behind Sentiment Analysis and to compare statistical methodologies for classifying Twitter sentiments.