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The terrorist attacks in Norway in 2011 and New Zealand in 2019 have revealed that the far-right worldwide uses the memory of the Yugoslav wars for online mobilization. Scholars working on memory activism usually deal with the liberal, self-critical memory emerging from the bottom-up activism of human rights groups while neglecting the activism of the far-right. This article fills the gap by addressing the global circulation of two memes, Remove Kebab and Pepe the Frog, as examples of far-right memory activism. In order to address the transnational circulation of memes as memory activism, this article employs the concept of ‘traveling memory’ while relying on multimodal discourse analysis to unveil the processes of memetic transformation, imitation, iconization and narrativization. The analysis reveals an alternative memory of Yugoslav wars that depicts Serbia as the first case of ‘white genocide’ in Europe, reversing the roles of war criminals and victims while propagating violence and celebrating genocide. The article argues that memory studies can no longer ignore memory production of far-right communities and, at the same time, outlines the method for examining far-right digital memory activism, revealing a whole set of mnemonic practices developed among the anonymous fringe communities of the far-right.

Incels (“involuntary celibates”) are online communities of young men, broadly aligned by anti-feminism, concern over an inability to form sexual relationships with women, and a strong negative focus on their own appearance. Incels have been linked to violent misogyny and several mass killings. Using critical discourse analysis on data from nine different incel online forums, this article explores how incels discussed the Plymouth shooting in August 2021, often reported as an incel attack, looking at the discourses which are invoked to justify or delegitimize violence. As well as violent rhetoric, our research also pays attention to anti-violent rhetoric in incel communities, an area not yet discussed in the literature regarding incels, but which may be invaluable to those hoping to address the issue of incel violence. Our findings identify significant differences in the way the shooting is discussed across different incel forums, and reveal that both pro and anti-violence discourses frequently invoke lookism and mental health to justify victimhood.

This paper maps communication channels exploited by the Salafi-jihadist violent extremist organisations (VEOs) and their followers between March 2020 and June 2022 on The Onion Router (TOR). It argues that the true scale of digital jihadist presence on TOR has remained insignificant for years. Militant Islamists have mostly used .onion domains as backup propaganda dissemination channels, which enable content takedown policies introduced by countering violent extremism stakeholders to be circumvented. Aside from propaganda distribution, TOR attracts Salafi-jihadist VEOs and their followers for other reasons, as it facilitates anonymous communication, crowdfunding, sharing of terrorist manuals or the organisation of terrorist attacks.

The journey inside Facebook’s semiosphere revolves around the present-day controversy on how algorithms foster polarization and discord in one of the biggest and most popular social media platforms, namely, Facebook. The present work focuses on the so-called Facebook Files as a specific case study. By drawing on these investigations, the present study discusses what are the principles used by the Facebook algorithms in order to select a certain type of content and to direct attention to it, whilst generally discarding other types of content considered not enough engaging. By drawing on the perspective of the semiotics of culture, this paper makes an analogy between Ju. Lotman’s model of the “semiosphere” and the Facebook’s digital semiosphere with the goal of unpacking how the selection, diffusion, and suppression of online content is geared towards the polarization of ideas.

Since the beginning of 2020, while societies and economies around the world have struggled to cope with the realities of the COVID-19 pandemic, cyberspace has given governments, businesses, and general end-users the ability to work, play, and connect in new and innovative ways. With everything from workspaces and classrooms to family gatherings and exercise routines forced online, the Internet has enabled people across the globe to carry on and maintain a sense of normalcy during very abnormal times. However, at the same time, while the world has been focused on the health, economic, political, and social ramifications of the pandemic, terrorist organizations, fringe groups, and extremist communities around the world have become emboldened, finding opportunity to exploit the situation, incite hate, (re)mobilize, and promote their ideologies online in novel ways. These groups—which we loosely classify as malicious nonstate actors for the purposes of this research —have been primarily focused on exploiting and contributing to the diffusion of information during the pandemic for their own strategic gain.

Ephemeral digital trace data can decrease the completeness, reproducibility, and reliability of social media datasets. Systematic post deletions thus potentially bias the results of computational methods used to map actors, content, and online information diffusion. Therefore, the aim of this study was to assess the extent and distribution of message deletion across different data types using data from the hybrid messenger service Telegram, which has experienced an influx of deplatformed users from mainstream social media platforms. A repeatedly scraped sample of messages from public Telegram groups and channels was used to investigate the effect of message ephemerality on the consistency of Telegram datasets. The findings revealed that message deletion introduces biases to the computational collection and analysis of Telegram data. Further, message ephemerality reduces dataset consistency, the quality of social network analyses, and the results of computational content analysis methods, such as topic modeling or dictionaries. The implications of these findings for scholars aiming to use Telegram data for computational research, possible solutions, and contributions to the methodological advancement of studying online political communication are discussed further in this article.