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This article uses the context of the widespread circulation of accounts about “CoronaJihad” in India during the COVID-19 pandemic to examine how public WhatsApp groups that participate in disseminating such accounts function within the ecosystem of hate around Hindutva majoritarianism in the country. The manner in which the WhatsApp platform operates within this ecosystem is mapped through a granular study of three public Hindutva WhatsApp groups; the messages within these groups during the first phase of the COVID-19 lock-down in India were examined during the course of this study. The pattern of messaging within the three groups that contribute to the narrative of “CoronaJihad,” which blames the minority Muslim community for the spread of the virus in India, were analyzed. The article focuses on factors including company policies and the specific sociopolitical situation in the country to understand the circumstances that make WhatsApp’s deep entanglement with the divisive politics of Hindutva majoritarianism in India possible.

WhatsApp is the most popular messaging app in the world. Due to its popularity, WhatsApp has become a powerful and cheap tool for political campaigning being widely used during the 2019 Indian general election, where it was used to connect to the voters on a large scale. Along with the campaigning, there have been reports that WhatsApp has also become a breeding ground for harmful speech against various protected groups and religious minorities. Many such messages attempt to instil fear among the population about a specific (minority) community. According to research on inter-group conflict, such `fear speech’ messages could have a lasting impact and might lead to real offline violence. In this paper, we perform the first large scale study on fear speech across thousands of public WhatsApp groups discussing politics in India. We curate a new dataset and try to characterize fear speech from this dataset. We observe that users writing fear speech messages use various events and symbols to create the illusion of fear among the reader about a target community. We build models to classify fear speech and observe that current state-of-the-art NLP models do not perform well at this task. Fear speech messages tend to spread faster and could potentially go undetected by classifiers built to detect traditional toxic speech due to their low toxic nature. Finally, using a novel methodology to target users with Facebook ads, we conduct a survey among the users of these WhatsApp groups to understand the types of users who consume and share fear speech. We believe that this work opens up new research questions that are very different from tackling hate speech which the research community has been traditionally involved in.

This study tests whether social media disinformation contributes to domestic terrorism within countries. I theorize that disinformation disseminated by political actors online through social media heightens political polarization within countries and that this, in turn, produces an environment where domestic terrorism is more likely to occur. I test this theory using data from more than 150 countries for the period 2000–2017. I find that propagation of disinformation through social media drives domestic terrorism. Using mediation tests I also verify that disinformation disseminated through social media increases domestic terrorism by, among other processes, enhancing political polarization within society.

The counterterrorism and CVE community has long questioned the effectiveness of counterspeech in countering extremism online. While most evaluation of counterspeech rely on limited reach and engagement metrics, this paper explores two models to better measure behavioral change and sentiment analysis. Conducted via partnerships between Facebook and counter-extremism NGOs, the first model uses A/B testing to analyze the effects of counterspeech exposure on low-prevalence-high-risk audiences engaging with Islamist extremist terrorist content. The second model builds upon online safety intervention approaches and the Redirect Method through a search based “get-help” module, redirecting white-supremacy and Neo-Nazi related search-terms to disengagement NGOs.

Several alternative social media platforms have emerged in response to perceptions that mainstream platforms are censoring traditional conservative ideologies. However, many of these alternative social media platforms have evolved to be outlets for hate speech and violent extremism. This study examines hate-based channels on Telegram from a US perspective. While Telegram has often been studied in relation to ISIS, less is known about its usage by US extremist users and movements. The authors used OSINT and observational methods on a sample of 125 Telegram channels containing hate speech and violent extremist content from far-right and far-left perspectives. The authors hypothesized that there would be a greater and growing presence of far-right activity compared to farleft activity due to current migration trends away from mainstream social media by the far-right. The authors also sought to observe the presence of disinformation campaigns, conspiracy theories, and accelerationism on Telegram. This study had four major findings: (1) the findings supported the hypothesis that more channels were host to farright dialogues, yet there were several far-left channels present, (2) 64.8% of the channels grew in size over a oneweek period, (3) 47 of the 125 channels were connected to well-known violent extremist movements or hate groups, and (4) QAnon and the COVID-19 pandemic were the most prominent sources of disinformation and conspiracy theories on Telegram. The findings of this study highlight that alternative social media platforms are a growing environment for a range of hateful ideologies and are aiding the spread of disinformation campaigns. This study concludes with a discussion on future strategies to combat the influence of the Internet on radicalization outcomes.

In February 2019, Moonshot launched The Redirect Method with funding from the Community Resilience Fund and in collaboration with the Canada Centre for Community Engagement and
Violence Prevention at Public Safety Canada. Canada Redirect was first deployed across all 13 Canadian provinces and territories, and in June 2019 our campaigns were subdivided to incorporate 353 postcodes in Canada’s six largest cities. These localized campaigns enabled Moonshot to collect granular data on extremist search appetite, test experimental messaging, and
explore the viability of providing at-risk users with content and services in their community.

Using the updated Redirect Method, Canada Redirect aimed to reach at-risk users with content that aligned as closely as possible with what they were searching for. Moonshot used subject-matter expertise and in-house knowledge to match relevant counter-narratives to their respective target audiences. This approach taps into a range of content ecosystems, such as music, gaming, and literature, to deliver alternative messaging that contrasts with the extremist content a user may be searching for, such as neo-Nazi manifestos or an ISIS nasheed. Moonshot adapted the Redirect Method to include content specific to the Canadian context in order to increase the relevance and impact of counter-narratives to the Canadian at-risk audience.

This report details Canada Redirect’s project phases, achievements, and findings from our digital campaigns, which were deployed across Canada for over a year, from 21 February 2019 to 23 March 2020.