Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions

Arsalan Mujahid Ghouri

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Type :	article
ISSN :	0254-5330
Main Author :	Arsalan Mujahid Ghouri
Title :	Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions

Place of Production :	Tanjung Malim
Publisher :	Fakulti Pengurusan dan Ekonomi
Year of Publication :	2023
Notes :	Annals of Operations Research
Corporate Name :	Universiti Pendidikan Sultan Idris
HTTP Link :	Click to view web link

Abstract : Universiti Pendidikan Sultan Idris

Fake news and disinformation (FNaD) are increasingly being circulated through various online and social networking platforms, causing widespread disruptions and influencing decision-making perceptions. Despite the growing importance of detecting fake news in politics, relatively limited research efforts have been made to develop artificial intelligence (AI) and machine learning (ML) oriented FNaD detection models suited to minimize supply chain disruptions (SCDs). Using a combination of AI and ML, and case studies based on data collected from Indonesia, Malaysia, and Pakistan, we developed a FNaD detection model aimed at preventing SCDs. This model based on multiple data sources has shown evidence of its effectiveness in managerial decision-making. Our study further contributes to the supply chain and AI-ML literature, provides practical insights, and points to future research directions. 2022, The Author(s).

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