Online Trolling: The Impact of Antisocial Online Content, Social Media Use, and Gender.

The present study aimed to observe the relationships between online trolling, exposure to antisocial online content, frequency of social media use, and gender, using the GAM as a theoretical framework. Four hundred twenty-nine Brazilian internet users (mean = 25.07 years; SD = 7.59; EP = 0.36), most of whom were women (71.8%), participated in the survey. Bivariate correlations indicated a positive relationship between online trolling, exposure to antisocial online content (r = 0.12; p < 0.01), Facebook use (r = 0.21; p < 0.01), Twitter Use (r = 0.12; p < 0.01), and gender (r = 0.15; p < 0.01). An explanatory model including these variables was tested, and obtained a significant model fit (GFI = 0.99; Comparative Fit-Index = 0.99; Tucker Lewis Index = 0.97; Root Mean Square Residual = 0.02; RMSEA = 0.02 | CI = 0 .01-0.07 |). Were also observed indirect effects for exposure to antisocial online content through Twitter use and Facebook use on trolling (λ = 0.03; CI = 0.01-0.05; p < 0.05). It is possible to conclude that the research objectives were fulfilled, emphasizing the role of situational variables in the understanding of online trolling.

Why do we share aggressive online content? Testing a short cycle model.

The present study aimed to observe the impacts of aggressive online content exposure and personality on aggressive content sharing, considering the mediating role of positive and negative affects. A total of 302 Brazilians, equally divided into two groups, participated in a social network simulation, being exposed to aggressive (experimental group) or neutral (control group) posts and choosing what they would like to share on this site (among aggressive or nonaggressive material). A factorial MANOVA showed a significant difference for positive and negative affects and aggressive content sharing (Wilks' Λ = 0.936; F[3, 298] = 6.812; p = .001; η2 = 0.064). Through structural equation modeling, an explanatory model was also tested, in which this behavior was directly predicted by aggressive online content exposure and suffered indirect effects from openness, conscientiousness, and extroversion, mediated by positive affects (goodness-of-fit index = 0.997, comparative fit-index = 0.998, Tucker-Lewis index = 0.996, SRMR = 0.028, root-mean-square error of approximation = 0.035, CI = 0.003-0.054). It is possible to conclude that the objectives are met, highlighting the contribution to understanding aggressive online behavior through the proximal processes described in the general aggression model.