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

Pervaiz Akhtar; Arsalan Mujahid Ghouri; Haseeb Ur Rehman Khan; Mirza Amin ul Haq; Usama  Awan; Nadia  Zahoor; Zaheer Khan; Aniqa Ashraf

doi:10.1007/s10479-022-05015-5

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

Pervaiz Akhtar^* (Corresponding Author), Arsalan Mujahid Ghouri, Haseeb Ur Rehman Khan, Mirza Amin ul Haq, Usama Awan, Nadia Zahoor, Zaheer Khan, Aniqa Ashraf

^*Corresponding author for this work

Business Management

Research output: Contribution to journal › Article › peer-review

20 Citations (Scopus)

9 Downloads (Pure)

Abstract

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.

Original language	English
Pages (from-to)	633–657
Number of pages	25
Journal	Annals Of Operations Research
Volume	327
Early online date	1 Nov 2022
DOIs	https://doi.org/10.1007/s10479-022-05015-5
Publication status	Published - 1 Aug 2023

Keywords

Fake news
Disinformation
misinformation
Artificial intelligence
Machine learning
Supply chain disruptions
Effective decision making

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Cite this

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abstract = "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.",

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AU - Akhtar, Pervaiz

AU - Ghouri, Arsalan Mujahid

AU - Ur Rehman Khan, Haseeb

AU - Amin ul Haq, Mirza

AU - Awan, Usama

AU - Zahoor, Nadia

AU - Khan, Zaheer

AU - Ashraf, Aniqa

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AB - 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.

KW - Fake news

KW - Disinformation

KW - misinformation

KW - Artificial intelligence

KW - Machine learning

KW - Supply chain disruptions

KW - Effective decision making

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DO - 10.1007/s10479-022-05015-5

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JO - Annals Of Operations Research

JF - Annals Of Operations Research

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

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Keywords

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