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ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:1:11401 2025-05-08T17:16:14Z 1

Improving Fake News Detection on Social Media Platforms Using Modified Metaheuristics and Machine Learning 2024 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/1/11401 https://ieeexplore.ieee.org/abstract/document/10910761 L. Jovanovic N. Bacanin M. Antonijevic A. Jokic M. Zivkovic S. Malisic Social networking and emerging technologies have fundamentally reshaped personal connectivity online. Despite the increasing reliance on the internet for everyday tasks, entertainment, and community building by businesses, corporations, and individuals, online social interactions continue to pose challenges. Misuse of social platforms can lead to the spread of misinformation. This issue has brought the emergence of fake news to the forefront of societal concerns. The vast volumes of data and rapidly evolving language used on social media platforms render traditional approaches, like static filter lists, ineffective. This study proposes a data-driven approach leveraging applied AI to detect and mitigate online misinformation using advanced natural language processing (NLP) techniques. A modified particle swarm optimization (PSO) algorithm is introduced for hyperparameter optimization, demonstrating promising results in maximizing performance. A comparative analysis across several contemporary optimizers on a real-world dataset demonstrates the efficacy of the proposed approach, achieving an accuracy of 0.846620 with the best-optimized models. conferenceObject 1 6 10.1109/ICDDS62937.2024.10910761 2024 IEEE 3rd International Conference on Data, Decision and Systems (ICDDS), IEEE, Bangalore, India