Explore the vast range of titles available.

BACKGROUND: In 2013, Internet gaming disorder (IGD) was incorporated in the current version of the DSM-5. IGD refers to a problematic use of video games. Longitudinal studies on the etiology of IGD are lacking. Furthermore, it is currently unclear to which extent associated psychopathological problems are causes or consequences of IGD. In the present survey, longitudinal associations between IGD and adolescent and parental mental health were investigated for the first time, as well as the temporal stability of IGD. METHODS In a cross-lagged panel design study, family dyads (adolescent with a parent each) were examined in 2016 (t1) and again 1 year later (2017, t2). Overall, 1095 family dyads were assessed at t1 and 985 dyads were re-assessed at t2 with standardized measures of IGD and several aspects of adolescent and parental mental health. Data were analyzed with structural equation modeling (SEM). RESULTS Male gender, a higher level of hyperactivity/inattention, self-esteem problems and IGD at t1 were predictors of IGD at t2. IGD at t1 was a predictor for adolescent emotional distress at t2. Overall, 357 out of the 985 adolescents received a diagnosis of IGD at t1 or t2: 142 (14.4%) at t1 and t2, 100 (10.2%) only at t1, and 115 (11.7%) only at t2. CONCLUSIONS Hyperactivity/inattention and self-esteem problems seem to be important for the development of IGD. We found first empirical evidence that IGD could prospectively contribute to a deterioration of adolescent mental health. Only a subgroup of affected adolescents showed IGD consistently over 1 year.

We model the dynamics of discrimination and show how its evolution can identify the underlying source. We test these theoretical predictions in a field experiment on a large online platform where users post content that is evaluated by other users on the platform. We assign posts to accounts that exogenously vary by gender and evaluation histories. With no prior evaluations, women face significant discrimination. However, following a sequence of positive evaluations, the direction of discrimination reverses: women’s posts are favored over men’s. Interpreting these results through the lens of our model, this dynamic reversal implies discrimination driven by biased beliefs.

Automatically inferring user demographics from social media posts is useful for both social science research and a range of downstream applications in marketing and politics. We present the first extensive study where user behaviour on Twitter is used to build a predictive model of income. We apply non-linear methods for regression, i.e. Gaussian Processes, achieving strong correlation between predicted and actual user income. This allows us to shed light on the factors that characterise income on Twitter and analyse their interplay with user emotions and sentiment, perceived psycho-demographics and language use expressed through the topics of their posts. Our analysis uncovers correlations between different feature categories and income, some of which reflect common belief e.g. higher perceived education and intelligence indicates higher earnings, known differences e.g. gender and age differences, however, others show novel findings e.g. higher income users express more fear and anger, whereas lower income users express more of the time emotion and opinions.

Young athletes value their social relations in sports, and these social relations can have consequences when it comes to joining, continuing, and quitting sports. Yet the important question of how social relations in sports develop has not yet been adequately answered. Hence, we investigated how athletes' social relations in sports depend on social relations outside of sports: in leisure, school, and social media. A total of 387 athletes (aged 16-19) from 30 Norwegian sports groups completed a survey on electronic tablets. We asked how social relations in leisure, school, and social media-through the social mechanisms of contact, homophily, and contagion-influenced social relations in sports. We also controlled for the effect of exercise frequency and duration (years) of contact in sports. Exponential random graph modelling (ERGM) analyses showed that first and foremost, relations from social media and leisure, but also school networks and exercise frequency, influence sports networks. This study shows that social relations in sports are diverse and depend on social relations outside sports. We discuss how this has 'counterintuitive' consequences for sports participation, particularly the importance of supporting athletes' social relations outside of sports for the strengthening of social relations within sports when addressing challenges concerning recruitment, continuation, and dropout from sports. (Autor).

To understand the impact of social capital on knowledge integration and performance within digitally enabled teams, we studied 46 teams who had a history and a future working together. All three dimensions of their social capital (structural, relational, and cognitive) were measured prior to the team performing two tasks in a controlled setting, one face-to-face and the other through a lean digital network. Structural and cognitive capital were more important to knowledge integration when teams communicated through lean digital networks than when they communicated face-to-face; relational capital directly impacted knowledge integration equally, regardless of the communication media used by the team. Knowledge integration, in turn, impacted team decision quality, suggesting that social capital influences team performance in part by increasing a team's ability to integrate knowledge. These results suggest that team history may be necessary but not sufficient for teams to overcome the problems with the use of lean digital networks as a communication environment. However, team history may present a window of opportunity for social capital to develop, which in turn allows teams to perform just as well as in either communication environment.

In recognition of the empowering potential of digital technologies, gender equality in internet access and digital skills is an important target in the United Nations (UN) Sustainable Development Goals (SDGs). Gender-disaggregated data on internet use are limited, particularly in less developed countries. We leverage anonymous, aggregate data on the online populations of Google and Facebook users available from their advertising platforms to fill existing data gaps and measure global digital gender inequality. We generate indicators of country-level gender gaps on Google and Facebook. Using these online indicators independently and in combination with offline development indicators, we build regression models to predict gender gaps in internet use and digital skills computed using available survey data from the International Telecommunications Union (ITU). We find that women are significantly underrepresented in the online populations of Google and Facebook in South Asia and sub-Saharan Africa. These platform-specific gender gaps are a strong predictor that women lack internet access and basic digital skills in these populations. Comparing platforms, we find Facebook gender gap indicators perform better than Google indicators at predicting ITU internet use and low-level digital-skill gender gaps. Models using these online indicators outperform those using only offline development indicators. The best performing models, however, are those that combine Facebook and Google online indicators with a country's development indicators such as the Human Development Index.

The popularity of social networking sites (SNSs) among adolescents and young adults has raised concerns that the intensity of using these platforms might be associated with lower academic achievement. The empirical findings on this issue, however, are anything but conclusive. Therefore, we present four random-effects meta-analyses including 59 independent samples (total N = 29,337) on the association between patterns of SNS use and grades. The meta-analyses identified small negative effects of = - .07, 95% CI [- .12, - .02] for general SNS use and = - .10, 95% CI [- .16, - .05] for SNS use related to multitasking. General SNS use was unrelated to the time spent studying for school (= - .03, 95% CI [- 0.11, 0.06]) and no support for the time displacement hypothesis could be found in a meta-analytical mediation analysis. SNS use for academic purposes exhibited a small positive association, = .08, 95% CI [.02, .14]. Hypotheses with regard to cross-cultural differences were not supported. (ZPID).

No detailed description available for \"Twitter and Tear Gas\".

Public communication has become more important to higher education institutions (HEIs), with many HEIs using social media to communicate with stakeholders. However, scholarship on the subject is scarce and mainly based on single-platform studies and small datasets. Therefore, we conducted a cross-platform study to examine the communication of all Swiss HEIs on Facebook, Instagram, and Twitter. The results were based on two datasets: an automated analysis on data for all Swiss HEIs (n = 42) and their social media accounts from 2004 to 2021 (337,232 posts from 207 accounts), and a manual content analysis on 1,500 posts per platform. By including all HEIs in one country, this study allowed for a comparison of the results by HEI type: universities of applied sciences, universities of teacher education, and research universities. Results show that, in recent years, HEI communication increased on Instagram, but not on Facebook or Twitter. Twitter was used the most by research universities, while most Instagram and Facebook posts were from universities of applied sciences. Universities of teacher education were least active across all platforms. The content of communication across all HEI types was primarily self-referential. Our analysis of how well HEIs used the affordances of social media communication relative to hypertextuality and multimodality revealed a generally high level of adaption. Moreover, our data showed no substantial impact of the Covid-19 pandemic on posting activities and engagement with social media posts by HEIs for the two first years of the pandemic.

Adolescents frequently show risky behavior, and these problematic behavior patterns often do not occur in isolation, but together. Problematic alcohol use is widespread among youth, as is problematic use of the Internet and of specific online applications (video games or social media). However, there is still a lack of findings for minors regarding the relations between these behavioral patterns (particularly between problematic alcohol use and problematic gaming or problematic social media use). Standardized instruments were used to survey problematic alcohol use, problematic gaming, problematic social media use, problematic Internet use and mental health among 633 adolescents (mean age: 15.79 years). Bivariate correlation and multivariable linear regression analyses were conducted. The correlation analyses showed statistically significant positive bivariate relationships between all four behavioral patterns each. Antisocial behavior was related to all problematic behavioral patterns. Whereas, emotional distress, self-esteem problems and hyperactivity/inattention were associated with substance-unrelated problematic behavior patterns only. Anger control problems were related to problematic alcohol use and problematic gaming. In adolescence, the findings revealed small effect sizes between substance-related and substance-unrelated problematic behavior patterns, but moderate to large effect sizes within substance-unrelated behavioral patterns. Similarities and differences were found in the relations between the behavioral patterns and mental health.