Understanding the Roots of Radicalisation on Twitter

In an increasingly digital world, identifying signs of online extremism sits at the top of the priority list for counter-extremist agencies. Researchers and governments are investing in the creation of advanced information technologies to identify and counter extremism through intelligent large-scale analysis of online data. However, to the best of our knowledge, these technologies are neither based on, nor do they take advantage of, the existing theories and studies of radicalisation. In this paper we propose a computational approach for detecting and predicting the radicalisation influence a user is exposed to, grounded on the notion of ’roots of radicalisation’ from social science models. This approach has been applied to analyse and compare the radicalisation level of 112 pro-ISIS vs.112 “general" Twitter users. Our results show the effectiveness of our proposed algorithms in detecting and predicting radicalisation influence, obtaining up to 0.9 F-1 measure for detection and between 0.7 and 0.8 precision for prediction. While this is an initial attempt towards the effective combination of social and computational perspectives, more work is needed to bridge these disciplines, and to build on their strengths to target the problem of online radicalisation

Influence of augmented humans in online interactions during voting events

The advent of the digital era provided a fertile ground for the development of virtual societies, complex systems influencing real-world dynamics. Understanding online human behavior and its relevance beyond the digital boundaries is still an open challenge. Here we show that online social interactions during a massive voting event can be used to build an accurate map of real-world political parties and electoral ranks. We provide evidence that information flow and collective attention are often driven by a special class of highly influential users, that we name "augmented humans", who exploit thousands of automated agents, also known as bots, for enhancing their online influence. We show that augmented humans generate deep information cascades, to the same extent of news media and other broadcasters, while they uniformly infiltrate across the full range of identified groups. Digital augmentation represents the cyber-physical counterpart of the human desire to acquire power within social systems.Comment: 11 page

Online Radicalization Case Study of a Mass Shooting: the Payton Gendron Manifesto

On May 14th, 2022, 18-year-old Payton S. Gendron of Conklin, New York, drove his car more than 200 miles to a predominantly black neighborhood in Buffalo, New York. At around 2:30 p.m., Gendron arrived at a Tops supermarket wearing body armor, tactical gear and a helmet with a video camera attached. He utilized the camera to livestream the event and carried an AR-15 semi-automatic rifle because of its proven deadly nature. He began firing his assaultrifle in the parking lot of the supermarket, killing three victims. He then went inside the store where he killed a security guard and nine other shoppers before surrendering to police

Using Agent-Based Modelling to Address Malicious Behavior on Social Media

In this study we create a platform for evaluating social media policies through simulation. We argue that social media policies need to be tested and refined before they can be successfully applied. We propose agent-based modelling (ABM) as a method for representing both malicious and legitimate social media agents, along with their key behaviors. Our two main research questions are as follows. 1. How do we build an agent-based model of a social media platform to address social media regulation? 2. How can an agent-based simulation approach be used to assess the effectiveness of social media policies? A preliminary agent-based model has been implemented (in Python), using the five human user types (‘amplifier’, ‘broadcaster’, ‘commentator’, ‘influential user’ and ‘viewer’) and two bot types (‘simple’ and ‘sophisticated’). During the simulation, a social media network of 100 agents is created and the agents\u27 behaviors are captured in this paper

Malevolent Creativity & the Metaverse: How the immersive properties of the metaverse may facilitate the spread of a mass shooter’s culture

The innovation of the Metaverse heralds a new milestone in the Information Age as investors move forward with the plan to bring the metaverse to fruition. The metaverse will offer a heightened experience in terms of interactivity, economics, and platform, while paving the way for greater immersion through virtual reality and augmented reality technologies. It is likely that as the metaverse develops, gaming will offer a unique social experience through its features such as virtual worlds. Based on this, it is important for policymakers to look at extremist subcultures that will operate in the metaverse through these virtual features. Due to the role played by fringe subcultures in facilitating the recent mass shooting event in Buffalo, this article aimed to examine the main features of the metaverse and how its immersive properties could influence the creation of future metaversal subcultures that could act as a gateway towards future mass shooting incidents. To that end, it applied the model of malevolent creativity to the extremist use of online spaces to gain insight on how such properties could aid online extremists towards mobilization. Results show that the concatenation of malevolent creativity, innovation, and subcultural extremism may bridge the gap between ideation of mass shootings and mobilization. Based on this, the implication of this research suggests that tech entrepreneurs for the metaverse should be mindful of the risks that disconnection from the real-world society can create for young, isolated users and aim to implement safeguards in integral areas of the metaverse seven-layer chain, such as spatial computing, discovery, and the creator economy