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The Policy Brief and accompanying Guidance Note on utilizing online data to prevent violent extremism and hate speech apply the lessons learned from UNDP practitioners working on Preventing Violent Extremism (PVE) across seven country offices by undertaking pilot projects that collect, analyse and apply online data to their programming. The Policy Brief outlines the major structural, technical, and ethical challenges faced by the practitioners, analyses relevant existing policy frameworks, and explores the potential of human rights-compliant data driven methods to inform PVE programming by offering policy considerations and recommendations to decision-makers. The Guidance Note offers an overview of key processes, tools, and resources for practitioners to consider when utilizing online data for PVE and addressing hate speech. It promotes risk management as an inherently enabling process for enhancing the evidence base for PVE programming.

Terrorist groups have proved in recent years that they are particularly adept at
utilizing the Internet and social media to facilitate their activities, including incitement
to commit a terrorist act, radicalization to violence, recruitment, training, planning,
collection of information, communication, preparation, financing and execution of
attacks. In addition to Al-Qaida, one terrorist entity that has benefited significantly from
ICT is the Islamic State in Iraq and the Levant (ISIL), also known as Daesh. ISIL and its
supporters exploit the Internet as a means to broadcast its ideology and has made effective
use of the vast reach and rapidly evolving communications environment provided by
social media applications, which also serve as a highly effective tool for ISIL recruiters,
who have succeeded in attracting a global pool of around 25,000 foreign fighters from
over 100 States.

This document sets up the main recommendations identified through the three years of engagement and dialouge on this topic. It is anchored in the discussions from the round tables. It further builds on the experiences from UN field presences that are working to address these challenges at country level. The paper is the result of a cooperation between my Office and the ESRC Human Rights, Big Data and Technology Project at the University of Essex. I would like to especially thank Ahmed Shaheed, Deputy Director, Essex Human Rights, Big Data and Technology Project and former United Nations Special Rapporteur on Freedom of Religion or Belief for this partnership over the last several years and which has resulted in this policy paper.

The Secretary-General has the honour to transmit to the General Assembly the report prepared by the Special Rapporteur on the promotion and protection of the right to freedom of opinion and expression, David Kaye, submitted in accordance with Human Rights Council resolution 34/18. In this report, the Special Rapporteur evaluates the human rights law that applies to the regulation of online ‘hate speech’.

This work explores personalities of individuals at risk of Islamist radicalisation. Previous studies have successfully identified radicalised individuals on social media. However, a more prophylactic approach to counter radical communities would be to detect individuals prior to getting radicalised. A manually annotated dataset of 15,195 tweets from 259 persons believed to be at risk of radicalisation was classified according to Big 5 personality traits and compared to the same number of non-radical users. The results show that risk users can successfully be identified and exhibit distributional differences compared to non-radical users for Extraversion and Openness.

This Thesis contributes by proposing a method for identifying users believed to be at risk of radicalisation on social media, by utilising the social media networks of already radicalised individuals and a set of indicators derived from related work on radicalisation. In addition, this Thesis provides a new to the field, in-depth analysis of the personality traits of Twitter users at risk of radicalisation and how they may differ from ordinary users. The results show that the proposed data collection and annotation scheme is able to successfully identify individuals at risk of radicalisation, yielding an inter-annotator agreement, measured by Cohen’s Kappa, of 0.83. The analysis of the predicted personality traits shows that users at risk of radicalisation have common profiles for agreeableness and conscientiousness. When comparing the predicted traits to that of ordinary, non-radical Twitter users, the predictions show a marginal difference in distribution for agreeableness, openness, and conscientiousness, indicating a certain difference in personality between the two domains.