Quantum-inspired firefly algorithm with ant miner plus for fake news detection

Kanta Prasad Sharma (), A. Sai Manideep (), Shailesh Kulkarni, J. Gowrishankar (), Binod Kumar Choudhary (), Jatinder Kaur () and Anita Gehlot ()
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Kanta Prasad Sharma: Department of Computer Engineering and Application, GLA University, Mathura, Uttar Pradesh 281406, India
A. Sai Manideep: Department of Management Studies, Vignan’s Foundation for Science, Technology and Research, Vadlamudi, Andhra Pradesh, India
Shailesh Kulkarni: Department of Electronics and Telecommunication Engineering, Vishwakarma Institute of Information Technology, Pune, India
J. Gowrishankar: Department of Computer Science Engineering, School of Engineering and Technology, JAIN (Deemed to be University), Bangalore, Karnataka, India
Binod Kumar Choudhary: Department of Electrical and Electronics Engineering, ARKA Jain University, Jharkhand, India
Jatinder Kaur: Department of Electrical Engineering, Vivekananda Global University, Jaipur, Rajasthan 303012, India
Anita Gehlot: Department of Electronics & Communication Engineering, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun 248007, India

International Journal of Modern Physics C (IJMPC), 2025, vol. 36, issue 01, 1-24

Abstract: Nowadays, technology has shifted the way individuals access news from conventional media sources to social media platforms. The active engagement of people with social media platforms leads them to consume news without confirming its source or legitimacy. This facilitated the dissemination of more manipulated and false information in the form of rumors and fake news. Fake news can affect public opinion and create chaos and panic among the population. Thus, it is essential to employ an advanced methodology to identify fake news with high precision. This research work has proposed the concept of the quantum-inspired firefly algorithm with the ant miner plus algorithm (QFAMP) for more effective fake news detection. The proposed QFAMP algorithm utilizes the attributes of quantum computing (QC), the firefly algorithm (FA), and the ant miner plus algorithm (AMP). Here, the QFA approach ensures the effective exploitation of the firefly agents until the agents are able to search for the brighter firefly. Further, the AMP algorithm utilizes the best ants with higher pheromone concentrations for global exploration, which also avoids the premature convergence of the QFA agents. In addition, the AMP algorithm serves as an efficient data mining variant that is effective for the classification of fake news. The efficacy of the proposed QFAMP algorithm is evaluated for the dataset of FakeNewsNet, which is composed of two sub-categories: BuzzFeed and PolitiFact. The experimental evaluations indicate the effective performance of the proposed algorithm compared to the other techniques.

Keywords: Quantum computing; metaheuristic algorithms; firefly algorithm; quantum firefly algorithm; ant colony optimization; ant miner plus; fake news detection; optimization (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0129183124501742

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