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

C-Feel-It, a system which can tap opinion content in posts from the micro-blogging website, Twitter, is described and a qualitative evaluation of this system is presented based on a human-annotated tweet corpus.

Abstract

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. 1