The article builds on previous research concerning crisis discourse to explore both overt and subtle discriminatory discursive practices and realisations in climate change crisis contexts. Recognising that climate change constitutes a social, cultural and political crisis and that the term crisis itself entails a significant discursive shift in climate change communication, this study analyses a purpose-built corpus representing discourse surrounding the 2019–2020 Australian bushfire crisis on the platform Twitter (now X). It adopts a corpus-based appraisal and critical discourse analysis approach to social media discourse to conduct an in-depth examination of the discursive practices and overt/covert realisations of hate, affection and positive/negative solidarity that emerged during the crisis. Its ultimate aim is to demonstrate that the discursive struggles underpinning environmental and climate change crisis communication require deeper analysis, particularly to understand how specific frames and narratives may either exacerbate social division or foster solidarity in times of crisis.
This article explores analytically how articulation and recontextualisation of a specific form of ‘borderline discourse’ has been pivotal in political mainstreaming of illiberal views of contemporary far-right regarding immigration. Looking into borderline discourse dynamics in the context of social media – specifically of Twitter/X – the article explores critically how its use in party-political communication would, over time, facilitate the eventual spread as well as mainstreaming of illiberal far-right ideas and notions across the wider political spectrum. Analysing Tweets of the Swedish parliamentary political parties in the period 2010–2022, the article showcases how their political communication on social media would not only become preoccupied with immigration but also how a variety of positions ranging from ‘immigration-realist’ to overtly anti-immigration ones would become anchored across the Swedish political spectrum. While the far-right would still emerge as initiator and key articulator of many views on immigration – including those known from the wider contemporary international illiberalism – we also point to the role played in the process by other parties. We show thereby how far-right ideas eventually become recontextualised across the political spectrum thus contributing to the mainstreaming of the far right and its rhetoric and to the eventual general normalization of illiberal, imigration-related views.
This article investigates a media firestorm that broke out when a Swedish politician reposted material that was perceived by some as outright antisemitic and by others as a critique of antisemitic tropes. Our aim is threefold. Firstly, from an empirical perspective, we unpack the discursive contention surrounding the relationship between written language and image as potentially separate carriers (or not) of antisemitic meanings in digital environments. Secondly, on a theoretical level, we argue for the analytical value of bringing the Multimodal Discourse‑Historical Approach (MDHA) to Critical Discourse Studies into dialogue with a linguistic‑anthropological conceptualization of indexical misrecognition. MDHA helps trace how historically sedimented antisemitic tropes are multimodally constructed and recontextualized, while indexical misrecognition helps explain how different social actors arrive at competing interpretations of the same multimodal ensemble. Thirdly, methodologically, our analysis offers a cautionary counterpoint to corpus‑based, detection‑oriented paradigms of identifying antisemitic discourse; it underscores the need for quantitative hate‑speech analysis to move beyond isolated utterances and images and instead attend to the often ambivalent, latent, and contested nature of text/image nexus points on digital platforms.
In the contemporary landscape, driven by populism and polarisation, misinformation has emerged as a critical concern, particularly due to its documented link to the proliferation of hate speech and the hostility to which lying can lead. Fake news stories circulating online can influence attitudes, perceptions, and behaviours, and allegedly have led to political crises and instability, even putting democracy at risk. With this in mind, this paper delves into the interplay between migration and fake news, and sheds light on the dynamics that mould public opinion, and foster hatred and suspicion towards migrants. Embracing an interdisciplinary approach, we examine the mechanisms by which fake news and conspiracy theories exploit anti-migration narratives, with the result of influencing public discourse, setting political agendas and impacting social cohesion. To this end, we draw upon the principles of Nutcracker , a semi-supervised algorithm developed to detect and analyse social media profiles that propagate extremist content and disinformation, across topical domains, including migrants and governmental migration policies; for further annotation, we also use the free platform Label Studio . The data reveal that migrants are frequently misrepresented through fake narratives that neglect the complex drivers of migration and their contributions to host societies. Among the strategies used to portray the social actors in our X migration corpus are the following: Migrants are depicted as economic burdens, threats to local employment, or are associated with illegality, criminality and terrorism; additionally, their nationality, religion and physical appearance are problematised, which helps reinforce exclusionary and stereotypical discourses. Undeniably, all this can foster xenophobia, and exacerbate societal divisions, ignoring the nuanced reality of migration. Thus, alongside refining the algorithm, developing a taxonomy of fakespeech and improving hate speech detection, this study aims to show how disinformation and hate speech intersect in migration discourse, with implications for political, media and educational contexts.
This paper examines how hate speech towards Chinese Muslims is constructed in Chinese and American broadsheets. The analysis encompasses 6336 articles (5.4 million words) published between 2001 and 2024. It employs a combination of discursive shifts theory, BiCHAT detection and LLM-assisted corpus-based discourse analysis to uncover patterns in the media coverage. Findings reveal that Chinese outlets showed higher hate speech probabilities targeting specific subgroups, while American newspapers portrayed Chinese Muslims monolithically. Both weaponised the concepts of violence and terrorism alongside nationally distinct topoi. Probabilities declined until 2014, then resurged in Chinese newspapers, while peaking in 2016 before decreasing in American outlets. These differences reflected distinct topoi usage across three discursive shifts. Chinese newspapers shifted from security threats to social impacts and, finally, to institutional measures. American outlets progressed from ethnic othering to sociopolitical burden to active threat. This study demonstrates the nexus between discriminatory discourse and China’s stability maintenance policies.
