Article: Harmony amidst division: leveraging genetic algorithms to counteract polarisation in online platforms Journal: International Journal of Computational Science and Engineering (IJCSE) 2025 Vol.28 No.7 pp.1 - 17 Abstract: While facilitating global communication, social media platforms often exacerbate ideological polarisation, contributing to echo chambers and filter bubbles that hinder constructive discourse. This paper presents a novel approach using genetic algorithms (GAs) to mitigate polarisation in online social networks. Unlike traditional methods that offer static, symptom-based solutions, the GA-driven model dynamically identifies and modifies influential nodes to reduce polarisation while preserving network integrity. Optimising interactions among key nodes enhances diversity and fosters more inclusive dialogue. The model is validated using real-world datasets, including Polbooks and Polblogs networks, demonstrating significant polarisation reduction with minimal disruption to the network structure. The approach advances the theoretical understanding of polarisation mitigation and provides practical applications for designing recommendation systems that promote healthier, more diverse online communities. The study emphasises the potential of interdisciplinary methodologies, integrating computational algorithms with social science insights to create a more balanced and engaging digital environment. Inderscience Publishers - linking academia, business and industry through research

Title: Harmony amidst division: leveraging genetic algorithms to counteract polarisation in online platforms

Authors: Zaka Ul Mustafa; Muhammad Amir; Manal Mustafa; Muhammad Adnan Anwar

Addresses: International Islamic University Islamabad, Islamabad, Pakistan ' International Islamic University Islamabad, Islamabad, Pakistan ' Zaman Technologies Pvt Limited, Pakistan ' Department of Mathematics (CEMAT), IST – Instituto Superior Técnico, Ulisboa, Portugal

Abstract: While facilitating global communication, social media platforms often exacerbate ideological polarisation, contributing to echo chambers and filter bubbles that hinder constructive discourse. This paper presents a novel approach using genetic algorithms (GAs) to mitigate polarisation in online social networks. Unlike traditional methods that offer static, symptom-based solutions, the GA-driven model dynamically identifies and modifies influential nodes to reduce polarisation while preserving network integrity. Optimising interactions among key nodes enhances diversity and fosters more inclusive dialogue. The model is validated using real-world datasets, including Polbooks and Polblogs networks, demonstrating significant polarisation reduction with minimal disruption to the network structure. The approach advances the theoretical understanding of polarisation mitigation and provides practical applications for designing recommendation systems that promote healthier, more diverse online communities. The study emphasises the potential of interdisciplinary methodologies, integrating computational algorithms with social science insights to create a more balanced and engaging digital environment.

Keywords: echo chamber; filter bubble; digital social networks; social network analysis; polarisation; diversity; community discovery.

DOI: 10.1504/IJCSE.2025.143956

International Journal of Computational Science and Engineering, 2025 Vol.28 No.7, pp.1 - 17

Received: 21 Mar 2024
Accepted: 31 Oct 2024
Published online: 15 Jan 2025 *

Title: Harmony amidst division: leveraging genetic algorithms to counteract polarisation in online platforms

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