News Article Analysis for Indian Election 2024

Singh, Utkarsh (2023) News Article Analysis for Indian Election 2024. Masters thesis, Dublin, National College of Ireland.

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Abstract

Given India's extensive and dynamic political landscape, elections there have long attracted attention from throughout the world. The Indian Election of 2024 was covered extensively in news outlets throughout the world. Analysts find it challenging to recognize patterns, emotions, and themes because there are millions of digital media articles. Public opinion has been impacted by news and analysis throughout history. In the US, UK, Germany, and India, journalism has advanced along with technology. Utilizing machine learning and deep learning to analyze news content is novel in the age of AI. Using Selenium and Beautiful Soup, the system effectively collects news articles from well-known search engines. Social media and Wikipedia articles are not included in the evaluation process to verify that the content is from reliable news sources. After gathering articles, the system uses the advanced Transformers library to analyze sentiment. The general attitude of the articles (positive, negative, or neutral) is assessed using a BERT-based model, indicating the media's broad viewpoint on election-related topics. The most frequently used themes in the thesis are displayed in word clouds and frequency bar charts. This visual method helps identify electoral themes and issues fast. Language identification and translation make sure the system can handle content in multiple languages in a country with a diverse linguistic population like India. In conclusion, this study offers a fresh approach to news article analysis in the context of the 2024 elections in India that could be used elsewhere. The results can influence political tactics, media attention, and voter sentiment in upcoming elections.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Menghwar, Teerath Kumar UNSPECIFIED
Uncontrolled Keywords:	Selenium; Beautiful Soup; BERT; Indian Elections 2024
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	03 Jan 2025 13:53
Last Modified:	03 Jan 2025 13:53
URI:	https://norma.ncirl.ie/id/eprint/7274

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