Automatic detection of online hate speech serves as a crucial step in the detoxification of the online discourse. Moreover, accurate classification can promote a better understanding of the proliferation of hate as a social phenomenon. While most prior work focus on the detection of hateful utterances, we argue that focusing on the user level is as important, albeit challenging. In this paper we consider a multimodal aggregative approach for the detection of hate-mongers, taking into account the potentially hateful texts, user activity, and the user network. We evaluate our methods on three unique datasets X (Twitter), Gab, and Parler showing that a processing a user's texts in her social context significantly improves the detection of hate mongers, compared to previously used text and graph-based methods. Our method can be then used to improve the classification of coded messages, dog-whistling, and racial gas-lighting, as well as inform intervention measures. Moreover, our approach is highly efficient even for very large datasets and networks.

Recent years have witnessed a swelling rise of hateful and abusive content over online social networks. While detection and moderation of hate speech have been the early go-to countermeasures, the solution requires a deeper exploration of the dynamics of hate generation and propagation. We analyze more than 32 million posts from over 6.8 million users across three popular online social networks to investigate the interrelations between hateful behavior, information dissemination, and polarised organization mediated by echo chambers. We find that hatemongers play a more crucial role in governing the spread of information compared to singled-out hateful content. This observation holds for both the growth of information cascades as well as the conglomeration of hateful actors. Dissection of the core-wise distribution of these networks points towards the fact that hateful users acquire a more well-connected position in the social network and often flock together to build up information cascades. We observe that this cohesion is far from mere organized behavior; instead, in these networks, hatemongers dominate the echo chambers -- groups of users actively align themselves to specific ideological positions. The observed dominance of hateful users to inflate information cascades is primarily via user interactions amplified within these echo chambers. We conclude our study with a cautionary note that popularity-based recommendation of content is susceptible to be exploited by hatemongers given their potential to escalate content popularity via echo-chambered interactions.

Over three decades, the Internet has grown from a small network of computers used by research scientists to communicate and exchange data to a technology that has penetrated almost every aspect of our day-to-day lives. Today, it is hard to imagine a life without online access for doing business, shopping, and socialising. A technology that has connected humanity at a scale never before possible has also amplified some of our worst qualities. Online hate speech spreads virally across the globe with short and long term consequences for individuals and societies. These consequences are often difficult to measure and predict. Online social media websites and mobile apps have inadvertently become the platform for the spread and proliferation of hate speech. "Hate speech is a type of speech that takes place online (e.g., the Internet, online social media platforms) with the purpose to attack a person or a group on the basis of attributes such as race, religion, ethnic origin, sexual orientation, disability, or gender."

Over three decades, the Internet has grown from a small network of computers used by research scientists to communicate and exchange data to a technology that has penetrated almost every aspect of our day-to-day lives. Today, it is hard to imagine a life without online access for business, shopping, and socialising. A technology that has connected humanity at a scale never before possible has also amplified some of our worst qualities. Online hate speech spreads virally across the globe with short- and long-term consequences for individuals and societies. These consequences are often difficult to measure and predict. Online social media websites and mobile apps have inadvertently become the platform for the spread and proliferation of hate speech.