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SentiRich: Sentiment Analysis of Tweets Based on a Rich Set of Features
Mohammed Jabreel, Antonio Moreno
137 - 146
10.3233/978-1-61499-696-5-137
Frontiers in Artificial Intelligence and Applications
Volume 288: Artificial Intelligence Research and Development
Abstract

This paper proposes the representation of tweets using a novel set of features, which include a bag of negated words and the information provided by seven lexicons. The polarity of tweets is determined by a classifier based on a Support Vector Machine. The system has been evaluated on the standard tweet sets used in the SemEval 2015 competition, obtaining results that, in most cases, outperform those of the state-of-the-art sentiment analysis systems.

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