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With the spread of social networks and their unfortunate use for hate speech, automatic detection of the latter has become a pressing problem. In this paper, we reproduce seven state-of-the-art hate speech detection models from prior work, and show that they perform well only when tested on the same type of data they were trained on. Based on these results, we argue that for successful hate speech detection, model architecture is less important than the type of data and labeling criteria. We further show that all proposed detection techniques are brittle against adversaries who can (automatically) insert typos, change word boundaries or add innocuous words to the original hate speech. A combination of these methods is also effective against Google Perspective – a cuttingedge solution from industry. Our experiments demonstrate that adversarial training does not completely mitigate the attacks, and using character-level features makes the models systematically more
attack-resistant than using word-level features.

Thought-provoking and timely, this book addresses the increasingly widespread issue of online political hatred in Europe. Taking an interdisciplinary approach, it examines both the contributions of new technologies, in particular social networks, to the rise of this phenomenon, and the legal and political contexts in which it is taking place. Giovanni Ziccardi also evaluates possible remedies for the situation, including both legal and technological solutions, and outlines the potential for a unified European framework to counter the spread of hatred online.

In considering how terrorist movements use the Internet, it is becoming increasingly apparent that we must move beyond predominantly descriptive overviews of the contents of websites to examine in more detail the notion of virtual communities of support and the functions of these for their members. Virtual communities in support of terrorist movements are real social spaces where people interact on a regular basis to disseminate their views, share their knowledge, and encourage each other to become increasingly supportive of movements that use terrorism to achieve their goals. Taken from a larger body of comparative qualitative research investigating the content and function of discourses created in virtual communities in support of terrorism, this article presents a thematic analysis of “Stormfront,” a virtual community of the radical right.

To prevent and counter the spread of illegal hate speech online, in May 2016, the Commission agreed with Facebook, Microsoft, Twitter and YouTube a “Code of conduct on countering illegal hate speech online”. The implementation of the Code of Conduct is evaluated through a regular monitoring exercise set up in collaboration with a network of organisations located in the different EU countries. Using a commonly agreed methodology, these organisations test how the IT companies are implementing the commitments in the Code.

To prevent and counter the spread of illegal hate speech online, in May 2016, the Commission agreed with Facebook, Microsoft, Twitter and YouTube a “Code of conduct on countering illegal hate speech online”. The implementation of the Code of Conduct is evaluated through a regular monitoring exercise set up in collaboration with a network of organisations located in the different EU countries. Using a commonly agreed methodology, these organisations test how the IT companies are implementing the commitments in the Code.

To prevent and counter the spread of illegal hate speech online, in May 2016, the Commission agreed with Facebook, Microsoft, Twitter and YouTube a “Code of conduct on countering illegal hate speech online”. The implementation of the Code of Conduct is evaluated through a regular monitoring exercise set up in collaboration with a network of organisations located in the different EU countries. Using a commonly agreed methodology, these organisations test how the IT companies are implementing the commitments in the Code.