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PurposeThis study seeks to establish a new framework for categorizing incivility, differentiating between explicit and implicit forms, and to investigate their respective abilities to proliferate and mobilize conversations, along with behavioral outcomes in various social contexts. Design/methodology/approachEmploying computational techniques, this research analyzed 10,145 protest-related threads from the HK Golden Forum, a prominent online discussion board in Hong Kong. FindingsOur analysis revealed divergent effects of explicit and implicit incivility on their diffusion, influences on deliberative discussions, and user participation. Explicit incivility was found to impede deliberative conversations, while implicit incivility tended to provoke more responses. Explicit uncivil expressions encouraged the propagation of incivility but reduced the likelihood of individual involvement. In contrast, implicit incivility had a stronger dampening effect on further uncivil comments and achieved greater thread popularity. The results showed strong associations between uncivil expressions and the contextual norms surrounding social movements. Originality/valueTheoretically, this research introduced a classification of incivility and underscored the importance of differentiating between implicit and explicit incivility by examining their effects on deliberation and engagement. Although previous studies have extensively covered explicit incivility, this study goes further by analyzing implicit incivility and comparing both forms of uncivil discourse in a less-studied context. Methodologically, the study developed a Cantonese dictionary to differentiate between two types of incivility, providing a practical reference for more nuanced analyses. By revealing how varying movement norms moderate the interplay between deliberative and uncivil expressions, the study drew attention to the highly situational nature of incivility. 

Recent instances of lethal mass violence have been linked to digital communities dedicated to misogynist and sexist ideologies. These forums often begin with discussions of more conventional or mainstream ideas, raising the question about the process through which these communities transform from relatively benign to extremist. This article presents a study of the Reddit incel community, active from mid-2016 to its ban in late 2017, which evolved from a self-help forum to a hub for extremist ideologies. We use computational grounded theory to deduce empirical patterns in forum composition, psychological states reflected in language use, and semantic content before refining and testing an interactional process that explains this change: a shift away from drawing on real-world experiences in discussion toward a greater reliance on cognitively simple symbols of group membership. This shift, in turn, leads to more discussions centered on deviant ideology. The results confirm that understanding the dynamics of conversation—specifically, how ideas are interpreted, reinforced, and amplified in recurrent, person-to-person interactions—is crucial for understanding cultural change in digital communities. Implications for sociology of groups, culture, and interactions in digital spaces are discussed. 

When a group shares a viewpoint on a status order, their consensus imparts legitimacy to their shared understanding of that order. Conversely, a group espousing multiple viewpoints undermines the notion that one “true” hierarchy exists. To build empirical knowledge about how social groups contribute to the construction of status orders, we take the occupational hierarchy as a case study and map the structure of agreement across intersectional groups. First, we quantify the extent to which groups (1) agree internally on their occupational rankings (within-group consensus) and (2) agree with other groups (intergroup consensus). Using General Social Survey data on occupational perceptions, we find a cluster of privileged groups—namely, highly educated White men and women—who agree internally and with each other on the occupational status order. Lesser advantaged groups exhibit less internal agreement and do not cohere around an alternative conceptualization of value, leaving unchallenged the consensus of privileged groups. 

Sociological and urban studies have consistently reported that human behavior exhibits a discernible correlation with population size, following a power-law function. Individuals residing in larger communities exhibit significantly higher levels of activity in contrast to their counterparts in smaller communities. However, the underlying processes responsible for such behavioral patterns remain unclear. The authors propose that organizational crowding tends to generate competitive pressure that results in social overload for individuals, who in turn divide time and energy among many groups while reducing the time spent in each. The social overload thesis predicts integration, rather than mutual exclusion of groups, when experiencing competition. A large-scale event participation dataset from 11 major U.S. technology clusters over a period of 10 years is used to test these hypotheses. The results support the mediating role of competition in the relationship between population size and participation intensity. The authors demonstrate the impact of competition on network structure.