Paper: C-Feel-It: A Sentiment Analyzer for Micro-blogs

ACL ID P11-4022
Title C-Feel-It: A Sentiment Analyzer for Micro-blogs
Venue Annual Meeting of the Association of Computational Linguistics
Session System Demonstration
Year 2011

Social networking and micro-blogging sites are stores of opinion-bearing content created by human users. We describe C-Feel-It, a sys- tem which can tap opinion content in posts (called tweets) from the micro-blogging web- site, Twitter. This web-based system catego- rizes tweets pertaining to a search string as positive, negative or objective and gives an ag- gregate sentiment score that represents a senti- ment snapshot for a search string. We present a qualitative evaluation of this system based on a human-annotated tweet corpus.