GRENZE International Journal of Engineering and Technology
Vol. 11
(2025), Issue 1
Assessment of Sentiment and Text Mining of BBC News Channel Headlines
Authors
Amrutha Priya Ghantasala, Bhashvitha Reddy B, Sahithi P, Seshaeta P, P.V. Vara Prasad
Abstract
Text mining techniques are essential for uncovering patterns in large-scale textual databases. This research analyses BBC news headlines from 2022 and 2023, focusing on common themes and emotions. In 2022, word cloud analysis revealed themes like pandemic recovery, climate action, and geopolitical tensions. In 2023, the focus shifted to sustainability and social justice. Sentiment analysis consistently showed uncertainty, resiliency, and optimism, reflecting global affairs' dynamic nature. Cluster analysis identified key themes, with 2022 highlighting economic resilience and public health, while 2023 emphasized environmental stewardship and societal transformation. This study demonstrates the power of text mining in understanding socio-political currents and thematic trends in media discourse. By capturing intricate social, political, and law-and-order dynamics, especially during significant events like the Ukraine-Russia conflict, text mining proves crucial in revealing national perspectives and the interplay of global events within public discourse.
Pages:
4513 - 4519