Proceedings of the 2nd International Conference on Recent Advancement and Modernization in Sustainable Intelligent Technologies & Applications (RAMSITA-2026)

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Implementation and Evaluation of Enhanced CNN Algorithm for Fake News Detection

Authors
Shraddha Shah1, Sachin Patel2, *
1SAGE University, Indore, Madhya Pradesh, India
2SAGE University, Indore, Madhya Pradesh, India
*Corresponding author. Email: drsachinpatel.sage@gmail.com
Corresponding Author
Sachin Patel
Available Online 28 May 2026.
DOI
10.2991/978-94-6239-678-4_11How to use a DOI?
Keywords
Text Cleaning; Fake News Detection; Convolutional Neural Network; Deep Learning
Abstract

In this digital era transformation of digitalization creating unprecedented access to news and content globally. Advancement of technological some time facilitated and propagate of misinformation across online platforms as well as social media platforms. This kind of misleading content can disturb the economy level by purchasing in panic situation create damage in political environment due to create confusion among voters during election period also harm social atmosphere through spreading rumors in between friends, neighbors and relatives. This paper identifies distinctive patterns, textual characteristics, in addition to contextual indicators that distinguish among authentic and fabricated news content by implementing not only machine learning techniques but also various natural language processing (NLP) method. Preprocessing is a crucial step that transforms raw and unstructured data as an input into a usable format for machine learning models. Improved algorithm implements a comprehensive pre-processing pipeline with multiple stages. This document provides a comprehensive indication of all pre-processing and post-processing techniques implemented in the enhanced CNN-based fake news detection system. The improvements focus on enhancing text quality, feature representation, model architecture, and evaluation methodologies.

Copyright
© 2026 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 the 2nd International Conference on Recent Advancement and Modernization in Sustainable Intelligent Technologies & Applications (RAMSITA-2026)
Series
Advances in Intelligent Systems Research
Publication Date
28 May 2026
ISBN
978-94-6239-678-4
ISSN
1951-6851
DOI
10.2991/978-94-6239-678-4_11How to use a DOI?
Copyright
© 2026 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  - Shraddha Shah
AU  - Sachin Patel
PY  - 2026
DA  - 2026/05/28
TI  - Implementation and Evaluation of Enhanced CNN Algorithm for Fake News Detection
BT  - Proceedings of the 2nd International Conference on Recent Advancement and Modernization in Sustainable Intelligent Technologies & Applications (RAMSITA-2026)
PB  - Atlantis Press
SP  - 125
EP  - 136
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-678-4_11
DO  - 10.2991/978-94-6239-678-4_11
ID  - Shah2026
ER  -