Journal of Ubiquitous Computing and Communication Technologies
IRO Journals
Volume 4 — Issue 3 — September 2022

Sentiment Analysis and Topic Modeling on News Headlines

https://doi.org/10.36548/jucct.2022.3.008
Vijay Yadav
Department of Electronic and Computer Engineering, Institute of Engineering, Tribhuvan University, Lalitpur, Nepal
Subarna Shakya
Department of Electronic and Computer Engineering, Institute of Engineering, Tribhuvan University, Lalitpur, Nepal
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How to Cite

Yadav, Vijay, and Subarna Shakya. 2022. “Sentiment Analysis and Topic Modeling on News Headlines”. Journal of Ubiquitous Computing and Communication Technologies 4 (3): 204-18. https://doi.org/10.36548/jucct.2022.3.008.
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Keywords

— Sentiment analysis
— Topic modeling
— Data visualization
— Bi-LSTM
— LDA
— LSA
Published: 22-09-2022

Abstract

Sentiment analysis and topic modeling has wide range of applications from medical to entertainment industry, corporates, politics and so on. News media play vital role in shaping the views of public towards any product or people. The dataset used for this work is news headlines dataset of one of the leading new portals of India i.e., Times of India. This research aims to perform comparative study of both supervised and unsupervised learning for text analysis and use the best performing models in both the category for prediction of sentiment and topic classification of news headlines. For sentiment analysis, supervised techniques like Machine learning ensemble model and Bi-LSTM have used. Similarly, unsupervised techniques like LDA (Latent Dirichlet Allocation) and LSA (Latent Semantic Analysis) have been for topic modeling.

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