CLSIFeb 20, 2014

Detecting Opinions in Tweets

arXiv:1402.5123v18 citations
Originality Synthesis-oriented
AI Analysis

This addresses the need for automated opinion detection in social media data, but it is incremental as it applies existing methods to tweet classification.

The paper tackled the problem of classifying opinions in tweets as positive, negative, or neutral by using emoticons with a Bayesian method and adjectives/adverbs with Turney's method, achieving classification based on these features without reporting specific performance numbers.

Given the incessant growth of documents describing the opinions of different people circulating on the web, including Web 2.0 has made it possible to give an opinion on any product in the net. In this paper, we examine the various opinions expressed in the tweets and classify them positive, negative or neutral by using the emoticons for the Bayesian method and adjectives and adverbs for the Turney's method

Foundations

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