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.
Lo Giudice, M. V., Shadman Yazdi, A., Aziani, A., Evangelatos, S., Gousetis, N., Nikolopoulos, C., Informative (Dis)information: Exploring the Correlation Between Social Media Disinformation Campaigns and Real-World Criminal Activity, in 2024 5th International Conference in Electronic Engineering, Information Technology & Education (EEITE), (Chania (Creta), Grecia, 29-31 May 2024), IEEE, Chania (Creta), Grecia 2024: 1-6. [10.1109/EEITE61750.2024.10654415] [https://hdl.handle.net/10807/290676]
Informative (Dis)information: Exploring the Correlation Between Social Media Disinformation Campaigns and Real-World Criminal Activity
Lo Giudice, Michael Victor
Co-primo
Writing – Original Draft Preparation
;Aziani, AlbertoCo-primo
Writing – Original Draft Preparation
;
2024
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.