Sentiment Analysis of Students Feedback Using Lexicon Based Method and Hybrid Machine Learning Method

Authors

  • Shital A. Patil Research Scholar, Department of Computer Engineering, SSBT, COET, Jalgaon,
  • Krishnakant P. Adhiya Professor, Department of Computer Engineering, SSBT, COET, Jalgaon
  • Girishkumar K. Patnaik Professor, Department of Computer Engineering, SSBT, COET, Jalgaon

Keywords:

sentiment classification, feedback analysis, lexicon-based method, machine learning, feature extraction, feature selection, polarity detection

Abstract

Sentiment classification and opinion mining are the most widely used NLP applications for detection of human intention and reviews.  The use of social media is currently in high demand for the purpose of sharing information and interaction. This includes the textual and visual dissemination of feedback, emotions, and ideas. The most widely used social networks, such as Facebook, Twitter, and Instagram have become significant means for the exchange of knowledge and interaction among users who share a common interest group. The form of communication platform among these users may consist of large texts. In this day and age of advanced technological advances, people like to keep in touch with those they care about most by using a variety of social networking platforms. Many users are able to communicate their thoughts and feedback through on specific platform. In this paper we proposed a sentiment classification on the student feedback dataset using a hybrid machine learning algorithm in this work. The 9 different feature extraction methods, such as TF-IDF, N-Gram, NLP-based dependency features, and lexicon-based techniques, are used. The different machine learning algorithms are Naïve Bayes, ANN, SVM and HML classification algorithm. In a comparative analysis of the proposed system, the HML obtained higher classification accuracy of 98.20% with the lexicon-based method. The proposed model shows around 3-4% higher accuracy than the existing sentiment classification methodologies.

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References

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Published

12.01.2024

How to Cite

Patil, S. A. ., Adhiya, K. P. ., & Patnaik, G. K. . (2024). Sentiment Analysis of Students Feedback Using Lexicon Based Method and Hybrid Machine Learning Method. International Journal of Intelligent Systems and Applications in Engineering, 12(12s), 137–145. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4498

Issue

Vol. 12 No. 12s (2024)

Section

Research Article

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