Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)

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Automated News Summarization and Sentiment Insights

Authors
A. ShivaKumar1, *, Racharla Srujana1, Buddineni Vishwas1, Llati Aryan Reddy1
1Department of Information Technology, CMR College of Engineering and Technology, Hyderabad, Telangana, India
*Corresponding author. Email: ashivakumar@cmrcet.ac.in
Corresponding Author
A. ShivaKumar
Available Online 4 November 2025.
DOI
10.2991/978-94-6463-858-5_114How to use a DOI?
Keywords
News Summarization; Sentiment Analysis; VADER; LSA; Flask; Natural Language Processing
Abstract

The increased volume of online messages has made it difficult for users to efficiently process and extract relevant information. This paper presents a flask-based message summary system, allowing users to obtain accurate summary of news articles and simultaneously receive core meaning and context. The system extracts item content from a specific URL, creates extraction summary using latent semantic analysis (LSA), and evaluates the sense of the summarized text using Vader Sentiment analysis. Additionally, the system provides multilingual support using Google Translator and integrates the functionality of the Text-to-Speech for increased accessibility. Readability and understanding based on user settings. The sentiment analysis function categorizes the sound of an article as positive, neutral or negative, and providing users with insight into the emotional tendencies of news content. The GTTS library is used to convert summary into languages. This means systems, text overview techniques, and machine learning to improve news consumption for visually impaired people and users who prefer audio-based news consumption. With this implementation, we want to easily retrieve fast information, minimize read times, and improve user commitment with news content. Based on the ROUGE metrics, the version carried out an normal accuracy of 72.06% indicating a strong perfomance in keeping coherence in the generated summaries.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
Series
Advances in Computer Science Research
Publication Date
4 November 2025
ISBN
978-94-6463-858-5
ISSN
2352-538X
DOI
10.2991/978-94-6463-858-5_114How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - A. ShivaKumar
AU  - Racharla Srujana
AU  - Buddineni Vishwas
AU  - Llati Aryan Reddy
PY  - 2025
DA  - 2025/11/04
TI  - Automated News Summarization and Sentiment Insights
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 1372
EP  - 1382
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_114
DO  - 10.2991/978-94-6463-858-5_114
ID  - ShivaKumar2025
ER  -