Meta-level sentiment models for big social data analysis

@article{BravoMarquez2014MetalevelSM,
  title={Meta-level sentiment models for big social data analysis},
  author={Felipe Bravo-Marquez and Marcelo Mendoza and Barbara Poblete},
  journal={Knowl.-Based Syst.},
  year={2014},
  volume={69},
  pages={86-99}
}
People react to events, topics and entities by expressing their personal opinions and emotions. These reactions can correspond to a wide range of intensities, from very mild to strong. An adequate processing and understanding of these expressions has been the subject of research in several fields, such as business and politics. In this context, Twitter sentiment analysis, which is the task of automatically identifying and extracting subjective information from tweets, has received increasing… CONTINUE READING
Highly Cited
This paper has 112 citations. REVIEW CITATIONS
Tweets
This paper has been referenced on Twitter 1 time. VIEW TWEETS

Citations

Publications citing this paper.
Showing 1-10 of 58 citations

113 Citations

02040'14'15'16'17'18'19
Citations per Year
Semantic Scholar estimates that this publication has 113 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 34 references

Twitter sentiment classification using distant supervision

  • A. Go, R. Bhayani, L. Huang
  • Technical report Stanford University,
  • 2010
Highly Influential
6 Excerpts

The Nature of Emotions Human emotions have deep evolutionary roots, a fact that may explain their complexity and provide tools for clinical practice

  • R. Plutchik
  • American Scientist,
  • 2001
Highly Influential
5 Excerpts