Analyzing Educational Tweets using LDA Model

Authors

  • Sundravadivelu Kamatchi Research Scholar, Department of Computer Science, School of Information Technology, Madurai Kamaraj University,Madurai,Tamil Nadu, India-625 021
  • Thangaraj Muthuraman Professor, Department of Computer Science, School of Information Technology, Madurai Kamaraj University,Madurai, India-625 021

Keywords:

Topic modeling, Latent Dirichlet Allocation, Latent Semantic Analysis, Educational tweets

Abstract

For the purpose of generating best educational reforms, knowledge discovery of educational tweet analysis is more important. Today the social media content on the Internet is rigorously increasing hour by hour. Hence analyzing this textual content is a vital task to solve problems in education. In this study Latent Dirichlet Allocation (LDA) is used to analyze the text content which finds the relationships among documents in the corpus. This proposed work shows that the LDA provide better result to extract topic with accurate coherence & prevalence score. This work also infers that the LDA performs best than Latent Semantic Analysis (LSA).

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Published

16.12.2022

How to Cite

Kamatchi , S. ., & Muthuraman, T. . (2022). Analyzing Educational Tweets using LDA Model . International Journal of Intelligent Systems and Applications in Engineering, 10(4), 100–104. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2202

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Research Article