The Digital Analysis of Crimes Remaining in the Dark During the 2023 Earthquake Disaster Period in Turkey

Abstract

Objective: The aim of this study was to gain insights into crimes occurring in the dark figure during the earthquake disasters that took place in Turkey in 2023, measuring magnitudes of 7.4 and 7.6, within the context of post-disaster intervention and crime prevention efforts.

Methods: In this study, a qualitative analysis was conducted on crimes that remained obscured during the disaster period, targeting individuals using donation websites to provide financial aid to earthquake victims. By searching for a combination of content related to earthquake debris and '#crime types' on X Social Media Platform (formerly Twitter) for the year 2023, and examining fake donation websites using USOM data, these crimes were investigated.

Results: Within the scope of the study, crimes committed against earthquake victims that were most shared on X Platform with the highest hashtags(#) were identified as looting (65%) and theft (29%); whereas, concerning individuals sending financial aid to earthquake victims, it was determined that the most prevalent crime was qualified fraud.

Conclusion: During disaster periods, it is further believed that the establishment of prompt access barriers to illicit sites created for fraudulent purposes, supported by verification mechanisms utilizing deep learning technology for shared digital content, followed by the initiation of ex officio investigation processes, particularly targeting crimes such as looting, theft, and qualified fraud, and the formulation of crime-preventive policies, could serve in preventing such crimes and managing the perception of “unpunished crimes” in society during disaster periods.