Le Nguyen's Paper on Studying Spread of Radical Online Sentiment accepted at the WebConf companion Workshop, CySoc

Congratulations to Le Nguyen on a Paper Accept at the International Workshop on Cyber Social Threats (CySoc), a companion workshop at The Web Conference 2023.


Abstract:
The spread of radicalization through the Internet is a growing problem. We are witnessing a rise in online hate groups, inspiring the impressionable and vulnerable population towards extreme actions in the real world. In this paper, we study the spread of hate sentiments in online forums by collecting 1,973 long comment threads (30+ comments per thread) posted on dark-web forums and containing a combination of benign posts and radical comments on the Islamic religion. This framework allows us to leverage network analysis tools to investigate sentiment propagation through a social network. By combining sentiment analysis, social network analysis, and graph theory, we aim to shed light on the propagation of hate speech in online forums and the extent to which such speech can influence individuals. The results of the intra-thread analysis suggests that sentiment tends to cluster within comment threads, with around 75% of connected members sharing similar sentiments. They also indicate that online forums can act as echo chambers where people with similar views reinforce each other’s beliefs and opinions. On the other hand, the inter-thread shows that 64% of connected threads share similar sentiments, suggesting similarities between the ideologies present in different threads and that there likely is a wider network of individuals spreading hate speech across different forums. Finally, we plan to study this work with a larger dataset, which could provide further insights into the spread of hate speech in online forums and how to mitigate it.

Nidhi Rastogi
Nidhi Rastogi
Assistant Professor, GCCIS, RIT

My research interests in transdisciplinary work in Cybersecurity, Artificial Intelligence, Heterogeneous Networks, and Graph Analytics building systems at scale.