Laura G. E. Smith

Most research on online collective action investigates low‐effort, social media‐based actions rather than tactics with highly disruptive potential. To better account for the variety of forms of collective actions that use digital technologies, we conducted an open‐source intelligence search (Study 1a) and an expert consultation survey (Study 1b; N = 21), to create a database containing 31 types of actions. In Study 2, we interviewed activists ( N = 20) and found six key dimensions underlying those actions. In Study 3, participants ( N = 273) rated the actions across the dimensions. Based upon the (dis)similarities of each action's rating across the dimensions, we identified two main types and five subtypes of online collective actions: Ingroup‐assisting actions (collaborative resource generation, ingroup mobilization, and digital picketing) and outgroup‐attacking actions (disruptive clicktivism and technology‐enabled attacks). The results showed that digital collective actions substantively differ from each other based on the six underlying dimensions, from the social psychological function, to the skill required, to the groups being targeted. This work offers a multi‐dimensional explanation for the variations across the domain of online activism and offers a way forward for future collective action work to explore psychological motivations underlying choices across action type.

People perceive and respond to group threats in a variety of ways. To explain when, how, and why groups react, in this Review we integrate insights of research on the processes underlying perceived intergroup and intragroup threats, and their consequences. First, we examine how group members collectively appraise situations as threatening, including through group discussions. Second, we identify factors that explain perceptions of threat severity. Third, we review predictors and moderators of responses to identify the conditions that help predict when and how groups and group members react in specific ways. Evidence shows that perceived intergroup threats often lead to negative outcomes such as polarization and negative emotions, while fostering positive intragroup effects. In contrast, perceived intragroup threats, while emotionally challenging and potentially weakening the ingroup, may improve intergroup relations. We synthesise the evidence into a framework that explains how groups appraise and respond to perceived intergroup and intragroup threats.

Large language models (LLMs) are used by the public to summarize, recommend, and explain online content. To prevent generation of potentially harmful output and recommendations, most publicly accessible LLMs have implemented safeguards that are triggered when users ask for illegal content or proscribed groups. However, these models are pre-trained on data from the internet that may contain connections between benign and more extreme content and communities. Therefore, users may ask for seemingly innocuous content about alternative communities but receive potentially radicalizing output. To investigate this possibility, we conducted an experiment with two publicly available, widely used LLMs (OpenAI GPT 4o and Google Gemini). We systematically manipulated the nature of prompts asking for summarization of relatively benign content about the Tradwives community during a multi-turn conversation (N = 896). We show that benign prompts, especially those that involve roleplay and retrieval-augmented generation (RAG), can bypass safeguards and expose users to potentially radicalizing content and connections. The implication is that even with guardrails in place and users not intending to seek illegal content, LLMs could play a role in the radicalization process.

Governments around the world fear a loss of social cohesion and a risk of harm to individuals and democratic processes that stem from politicization , polarization and radicalization . We argue that these processes of social influence provide the motivation for—but are not sufficient for— mobilization (the behaviour of engaging in collective action). To be able to collectively act , people require the capability and resources to do so, which can be developed during an activation process. We clarify the common and distinct aspects of each process so the common drivers, but unique effects, can be conceptualized and operationalized by policymakers, practitioners and researchers who wish to understand democratic resilience.

This study investigates the pathways and predictors of piracy and cyberbullying among Korean adolescents using longitudinal data from 2003–2008. Findings reveal distinct trajectories and predictors for each behavior. This highlights the need for targeted interventions and challenges existing international cybercrime policies.

Inter‐brain synchrony occurs between individuals who feel connected socially, but how synchrony relates to felt connectedness under naturalistic social interaction has remained enigmatic. We hypothesized that inter‐brain synchrony between naturally interacting individuals might be associated with the internalization of a social identity, a link between an individual's personal identity and the social group to which the individual belongs. A convenience sample of sixty participants were split into dyads and interacted naturalistically on a social task. Through mapping EEG oscillatory waveforms onto a conceptual model categorizing the formation of a social identity within a naturalistic conversation, greater inter‐brain synchrony was observed in the emergent stage within the formation of a social identity compared to earlier stages, where a social identity was not present. We provide evidence for greater neural synchrony related to higher socio‐psychological connectedness during the development of social identity under naturalistic social interaction.

What motivates people to participate in collective action? Some actions such as symbolic or online actions are often critiqued as performative allyship, motivated by personal gain rather than genuine concern for the cause. We aim to adjudicate this argument by examining the quality of motivations for acting, drawing on the insights of self‐determination theory and the social identity approach. Using latent profile analysis, we examined whether there are different types of supporters of refugees based on their underlying motives. In Study 1, we surveyed supporters of Syrian refugees from six nations ( N = 936) and measured autonomous and controlled motivation, pro‐refugee identification and collective action. In Study 2 ( N = 1994), we surveyed supporters of Ukrainian refugees in Romania, Hungary and the UK. We found 4–5 profiles in each sample and consistently found that supporters with high autonomous motivation take more action than disengaged or ambivalent supporters (low/neutral on all motives). However, contrary to the tenets of self‐determination theory, those high in both autonomous and controlled motives were the most engaged. We conclude that the most committed supporters are those with multiple motives, but further research is needed on the role of controlled motivation.

Innovations in generative AI to create human-like text, images, and videos can cause social, psychological, and political harms. Here, we explain how psychologists can mobilize their extensive theoretical and empirical resources to better anticipate, understand, and mitigate those harms. Innovations in generative AI can cause social, psychological, and political harms. This Comment explains how psychologists can mobilize their extensive theoretical and empirical resources to better anticipate, understand, and mitigate those harms.

The term polarization is used to describe both the division of a society into opposing groups (political polarization), and a social psychological phenomenon (group polarization) whereby people adopt more extreme positions after discussion. We explain how group polarization underpins the political polarization phenomenon: Social interaction, for example through social media, enables groups to form in such a way that their beliefs about what should be done to change the world—and how this differs from the stance of other groups—become integrated as aspects of a new, shared social identity. This provides a basis for mobilization to collective action.