Indonesian social media sentiment analysis with sarcasm detection

@article{Lunando2013IndonesianSM,
  title={Indonesian social media sentiment analysis with sarcasm detection},
  author={Edwin Lunando and Ayu Purwarianti},
  journal={2013 International Conference on Advanced Computer Science and Information Systems (ICACSIS)},
  year={2013},
  pages={195-198}
}
Sarcasm is considered one of the most difficult problem in sentiment analysis. In our observation on Indonesian social media, for certain topics, people tend to criticize something using sarcasm. Here, we proposed two additional features to detect sarcasm after a common sentiment analysis is conducted. The features are the negativity information and the number of interjection words. We also employed translated SentiWordNet in the sentiment classification. All the classifications were conducted… CONTINUE READING
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Sistem Analisis Opini Microblogging Berbahasa Indonesia

  • Harlili, Wibisono, Yudi
  • Konferensi Nasional Sistem Informasi. Bali…
  • 2012
2 Excerpts

Thumb’s up? Sentiment Classification using machine learning Techniques

  • Pang, Bo, L. Lee, Vaithyanathan
  • Proceeding of the 7 Conference on Empirical…
  • 2002
2 Excerpts

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