The nexus between information disorder and terrorism: a mix of machine learning approach and content analysis on 39 terror attacks. Issue 3 (2nd September 2022)

• Record Type: Journal Article
• Authors: Chen, Xingyu Ken; Neo, Loo Seng; Ang, Anais; Lee, Jing Yi; Ong, Gabriel; Khader, Majeed
• Is Part Of: Dynamics of asymmetric conflict. Volume 15:Issue 3(2022)
• Page Start: 190
• Page End: 209
• Publication Date: 2022-09-02
• Subjects: Information disorder -- terrorism -- GTD -- machine learning -- southeast asia; Asymmetric warfare -- Periodicals; Genocide -- Periodicals; Terrorism -- Periodicals; Asymmetric warfare; Genocide; Terrorism; Periodicals; 355.02
• DOI: 10.1080/17467586.2022.2055097
• Languages: English
• ISSNs: 1746-7586

Abstract

ABSTRACT: A surge in the spread of fake news after a terror attack such as the 2018 Surabaya bombings has been observed in recent times. It was clear that the spread of fake news (i.e., information disorder [ID]) can amplify the social impact and consequences of a terror attack on the local community. However, research on the prevalence of ID in connection to a terror incident is not well-studied in Southeast Asia (SEA). To address this gap systematically, this study describes an approach taken to study this nexus between the spread of ID in connection to a terror attack. By drawing on the Global Terrorism Database and manual searches, a case study bank of 39 terror incidents with instances of ID in SEA from 2015 to 2019 was created through the use of a mix of automated and human workflows. This exploratory study sought to document the kinds of ID that emerged in English language media after a terror incident in SEA and to identify implications for the field of ID as well as terrorism