Recognizing Emotion in Text using Neural Network and Fuzzy Logic

  • Kanger N
  • et al.
N/ACitations
Citations of this article
11Readers
Mendeley users who have this article in their library.

Abstract

Objectives: To find out sentiment of people about a particular thing or objects and to classify these sentiments. Methods: The common dialect handling techniques like fuzzy logic and neural system to be used extract emotions from text present in various blogs using MATLAB. Findings: The results show that with Neural Network and Fuzzy Logic performs very well in recognizing the emotional polarity of the sentences. From result simulations it has been concluded that the proposed method worked well having accuracy of 90% and able to classify the text according to their class (Happy, Sad and Anger). Improvements: The proposed method achieves better results in terms of Accuracy, Precision, Sensitivity and Specificity.

Cite

CITATION STYLE

APA

Kanger, N., & Bathla, G. (2017). Recognizing Emotion in Text using Neural Network and Fuzzy Logic. Indian Journal of Science and Technology, 10(12), 1–6. https://doi.org/10.17485/ijst/2017/v10i12/100526

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free