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Although social media have become important venues for right-wing populist (RWP) campaigns, the content, selection, and effects of RWP messages on social media remain largely unknown. Using content and panel analysis in two studies, we investigated the potential reciprocal relationship between RWP communication on social media and citizens’ anti-immigrant attitudes, anti-elitist attitudes, and feelings of anger and anxiety. In Study 1, we analyzed 13,358 Facebook posts from German and Austrian political parties and their leading candidates. Among our results, RWP actors conveyed anti-immigrant and anti-elitist messages more often than non-RWP actors, and anti-immigrant messages especially induced negative emotional responses among followers of RWP actors. In Study 2, our analysis of data from a two-wave panel study with 559 respondents revealed that anti-immigrant attitudes drove selective exposure to RWP content on Facebook, which consequently fueled anti-immigrant attitudes, and that selective exposure to such content increased individuals’ anti-elitist attitudes and anxiety.

This paper, part of the Legal Perspectives on Tech Series, was commissioned in conjunction with the Congressional Counterterrorism Caucus.

To inform the discussion, the paper draws on the debates that have surrounded the U.K. ‘Encouragement of Terrorism’ criminal offence. Created by the Terrorism Act 2006, and recently amended by the Counter-Terrorism and Border Security Act 2019, this offence has proved controversial from its inception for two principal reasons. First, the offence expressly encompasses both direct and indirect encouragement. Critics have argued that the concept of indirect encouragement is too nebulous and gives the offence too wide a scope. Second, the framing of the offence focuses not on the purpose of the speaker, but on whether the potential effect of the statement is to encourage terrorism.

The advent of the Internet inadvertently augmented the functioning and success of violent extremist organizations. Terrorist organizations like the Islamic State in Iraq and Syria (ISIS) use the Internet to project their message to a global audience. The majority of research and practice on web‐based terrorist propaganda uses human coders to classify content, raising serious concerns such as burnout, mental stress, and reliability of the coded data. More recently, technology platforms and researchers have started to examine the online content using automated classification procedures. However, there are questions about the robustness of automated procedures, given insufficient research comparing and contextualizing the difference between human and machine coding. This article compares output of three text analytics packages with that of human coders on a sample of one hundred nonindexed web pages associated with ISIS. We find that prevalent topics (e.g., holy war) are accurately detected by the three packages whereas nuanced concepts (Lone Wolf attacks) are generally missed. Our findings suggest that naïve approaches of standard applications do not approximate human understanding, and therefore consumption, of radicalizing content. Before radicalizing content can be automatically detected, we need a closer approximation to human understanding.

The use of the internet for recruitment and the dissemination of violent extremist materials raises significant policy challenges for the European Union (EU), its Member States, and content sharing platforms (CSPs) 1 alike. This problem requires – through the eyes of the EU – a combination of legislative, non-legislative, and voluntary measures based on collaboration between authorities and CSPs with respect for fundamental (human) rights.

This paper, part of the Legal Perspectives on Tech Series, was commissioned in conjunction with the Congressional Counterterrorism Caucus.