“Brutal Kill!” Violent video games as a predictor of aggression

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.

The Psychological Implications of Companion Robots: A Theoretical Framework and an Experimental Setup

In this paper we present a theoretical framework to understand the underlying psychological mechanism involved in human-Companion Robot interactions. At first, we take the case of Sexual Robotics, where the psychological dynamics are more evident, to thereafter extend the discussion to Companion Robotics in general. First, we discuss the differences between a sex-toy and a Sexual Robots, concluding that the latter may establish a collusive and confirmative dynamics with the user. We claim that the collusiveness leads to two main consequences, such as the fixation on a specific and atypical type of sexual interaction, called paraphilic, and to the infantilization of the user, which we explain through the theoretical framework of "object-relation theory". We argue that these dynamics may degrade to an infantile stage the relational abilities of users, extending this argument to Companion Robots in general. Then, we enquire if and how the relational dynamics enacted in HRI may shift to human relations: we discuss the analogy with virtual reality concluding that, under certain condition, a symbolic shift might happen. In the last part of this work, we propose an experimental setup to verify if a collusive and confirmative interaction with a Companion Robot can, over time, impact on the user's ability to manage relational frustration.

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.