Informative (Dis)information: Exploring the Correlation Between Social Media Disinformation Campaigns and Real-World Criminal Activity

Michael Victor Lo Giudice*, Alberto Aziani, Spyridon Evangelatos, Nikolaos Gousetis, Christos Nikolopoulos

*Corresponding author

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The connection between online disinformation and crime is a topic of significant interest. An aspect of this topic, with strong research potential, is the causal relationship between crimes committed in the real world and disinformation spreading campaigns in the digital world, often on social media platforms. In essence, this research paper focuses on exploring said causal relationship, by seeking to establish a correlation between the diffusion of disinformation, online, and crimes committed offline; specifically, hate crimes. For this purpose, a novel method was employed: using robust machine learning algorithms for time-series predictions, in order to reveal causal pathways that traditional quantitative techniques may be unable to capture. Thus, the research conducted here exhibits AI applications in social science research and, at the same time, provides a greater understanding of the link between online disinformation and offline crime.
Original languageEnglish
Title of host publication2024 5th International Conference in Electronic Engineering, Information Technology & Education (EEITE)
Pages1-6
Number of pages6
DOIs
Publication statusPublished - 2024
Event2024 5th International Conference in Electronic Engineering, Information Technology & Education (EEITE) - Chania (Creta), Grecia
Duration: 29 May 202431 May 2024

Conference

Conference2024 5th International Conference in Electronic Engineering, Information Technology & Education (EEITE)
CityChania (Creta), Grecia
Period29/5/2431/5/24

Keywords

  • Convolutional Neural Networks
  • Crime Prediction
  • Deep Learning
  • Fake News and Disinformation
  • Machine Learning

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