SentiCircles for Contextual and Conceptual Semantic Sentiment Analysis of Twitter

@inproceedings{Saif2014SentiCirclesFC,
  title={SentiCircles for Contextual and Conceptual Semantic Sentiment Analysis of Twitter},
  author={Hassan Saif and Marta Fernandez Andres and Yulan He and Harith Alani},
  booktitle={ESWC},
  year={2014}
}
Lexicon-based approaches to Twitter sentiment analysis are gaining much popularity due to their simplicity, domain independence, and relatively good performance. These approaches rely on sentiment lexicons, where a collection of words are marked with fixed sentiment polarities. However, words’ sentiment orientation (positive, neural, negative) and/or sentiment strengths could change depending on context and targeted entities. In this paper we present SentiCircle; a novel lexicon-based approach… CONTINUE READING
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Key Quantitative Results

  • Our results show that our SentiCircle approach outperforms the other lexicon methods by nearly 20% in accuracy and 30-40% in F-measure.

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