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

被引：0
作者：
Pervaiz Akhtar
Arsalan Mujahid Ghouri
Haseeb Ur Rehman Khan
Mirza Amin ul Haq
Usama Awan
Nadia Zahoor
Zaheer Khan
Aniqa Ashraf
机构：
[1] University of Aberdeen Business School,Faculty of Management and Economics
[2] University of Aberdeen,Faculty of Art, Computing, and Creative Industry
[3] King’s College,Department of Business Administration
[4] Imperial College London,Department of Business Administration, Inland School of Business and Social Sciences
[5] Universiti Pendidikan Sultan Idris,School of Business and Management
[6] Universiti Pendidikan Sultan Idris,CAS
[7] Iqra University,Key Laboratory of Crust
[8] Inland Norway University of Applied Sciences,Mantle Materials and the Environments, School of Earth and Space Sciences
[9] Queen Mary University of London,Innolab
[10] University of Science and Technology of China,undefined
[11] University of Vaasa,undefined
来源：
Annals of Operations Research | 2023年 / 327卷
关键词：
Fake news; Disinformation; Misinformation; Artificial intelligence; Machine learning; Supply chain disruptions; Effective decision making;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：633 / 657
页数：24
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