Detecting Human Emovere through Data Mining

Authors

  • P Rani Dept. of CSE Aditya College Of Engineering, Madanapally, India
  • MV Jagannatha Reddy Dept. of CSE Aditya College Of Engineering, Madanapally, India
  • KSMV Kumar Dept. of CSE Aditya College Of Engineering, Madanapally, India
  • Sreedhar SB Dept. of CSE Aditya College Of Engineering, Madanapally, India

DOI:

https://doi.org/10.26438/ijcse/v8i1.6469

Keywords:

Human-Computer Interaction, Textual Emotion Recognition, speech analysis, twitter analysis, Emotion Word Ontology

Abstract

With the growth of the Internet community, textual data has proven to be the main tool of communication in humanhuman interaction. This communication is constantly evolving towards the goal of making it as human and real as possible. One way of humanizing such interaction is to provide a framework that can recognize the emotions present in the communication or the emotions of the involved users in order to enrich user experience. The use of social networking sites is one of the approaches for putting views of user. Proposed emotion detector system takes a text document or audio and the emotion word ontology as inputs and produces the scores of six emotion classes (i.e. happy, sad, fear, surprise, anger and disgust) as the output; for twitter data as input the extracted tweets are categorized in to positive, negative and neutral tweets.

References

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Published

2020-01-31
CITATION
DOI: 10.26438/ijcse/v8i1.6469
Published: 2020-01-31

How to Cite

[1]
P. Rani, M. J. Reddy, K. Kumar, and S. SB, “Detecting Human Emovere through Data Mining”, Int. J. Comp. Sci. Eng., vol. 8, no. 1, pp. 64–69, Jan. 2020.

Issue

Vol. 8 No. 1 (2020): IJCSE January Edition

Section

Research Article

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