The present study tests a recently proposed model in which social video game play supports wellbeing by contributing to a harmonious type of engagement with the game. Players (N = 2030) of the online-only multiplayer first-person shooter game, Destiny, reported the frequency they played with real-life friends, online-only friends and strangers, their type of engagement with the game – measured as harmonious and obsessive passion, and completed a wellbeing measure of social capital. \ud \ud Telemetry data also recorded their total time playing over the duration of the study. A structural equation model supported the prediction that harmonious – but not obsessive – passion would mediate the positive association between playing with others and social capital. \ud \ud The findings also supported a supplementary hypothesis that the three types of social relationships would be differentially associated with two forms of social capital – bridging versus bonding – as a function of the closeness of social ties. Real-life friends was positively associated with bonding, strangers with bridging, and online-only friends with both. \ud \ud Overall, these results emphasise that social interactions in (and around) online multiplayer video games are effective for building social capital, and do so by ensuring game play is in harmony with other goals and values

Financial institutions are interested in ensuring security and quality for their customers. Banks, for instance, need to identify and stop harmful transactions in a timely manner. In order to detect fraudulent operations, data mining techniques and customer profile analysis are commonly used. However, these approaches are not supported by Visual Analytics techniques yet. Visual Analytics techniques have potential to considerably enhance the knowledge discovery process and increase the detection and prediction accuracy of financial fraud detection systems. Thus, we propose EVA, a Visual Analytics approach for supporting fraud investigation, fine-tuning fraud detection algorithms, and thus, reducing false positive alarms.

Player motivation is a key research area within games research, with the aim of understanding how the motivation of players is related to their experience and behavior in the game. We present the results of a cross-sectional study with data from 750 players of League of Legends, a popular Multiplayer Online Battle Arena game. Based on the motivational regulations posited by Self-Determination Theory and Latent Profile Analysis, we identify four distinct motivational profiles, which differ with regards to player experience and, to a lesser extent, in-game behavior. While the more self-determined profiles “Intrinsic” and “Autonomous” report mainly positive experience-related outcomes, a considerable part of the player base does not. Players of the “Amotivated” and “External” profile derive less enjoyment, experience more negative affect and tension, and score lower on vitality, indicating game engagement that is potentially detrimental to players' well-being. With regards to game metrics, minor differences in the rate of assists in unranked matches and performance indicators were observed between profiles. This strengthens the notion that differences in experiences are not necessarily reflected in differences in behavioral game metrics. Our findings provide insights into the interplay of player motivation, experience, and in-game behavior, contributing to a more nuanced understanding of player-computer interaction.