University of Amsterdam

About: University of Amsterdam is a education organization based out in Amsterdam, Noord-Holland, Netherlands. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 59309 authors who have published 140894 publications receiving 5984137 citations. The organization is also known as: UvA & Universiteit van Amsterdam.

A six-factor structure of personality-descriptive adjectives: solutions from psycholexical studies in seven languages.

Abstract: Standard psycholexical studies of personality structure have produced a similar 6-factor solution in 7 languages (Dutch, French, German, Hungarian, Italian, Korean, Polish). The authors report the content of these personality dimensions and interpret them as follows: (a) a variant of Extraversion, defined by sociability and liveliness (though not by bravery and toughness); (b) a variant of Agreeableness, defined by gentleness, patience, and agreeableness (but also including anger and ill temper at its negative pole); (c) Conscientiousness (emphasizing organization and discipline rather than moral conscience); (d) Emotionality (containing anxiety, vulnerability, sentimentality, lack of bravery, and lack of toughness, but not anger or ill temper); (e) Honesty-Humility; (f) Intellect/Imagination/Unconventionality. A potential reorganization of the Big Five factor structure is discussed.

Put your money where your mouth is! : Explaining collective action tendencies through group-based anger and group efficacy

Abstract: Insights from appraisal theories of emotion are used to integrate elements of theories on collective action. Three experiments with disadvantaged groups systematically manipulated procedural fairness (Study 1), emotional social support (Study 2), and instrumental social support (Study 3) to examine their effects on collective action tendencies through group-based anger and group efficacy. Results of structural equation modeling showed that procedural fairness and emotional social support affected the group-based anger pathway (reflecting emotion-focused coping), whereas instrumental social support affected the group efficacy pathway (reflecting problem-focused coping), constituting 2 distinct pathways to collective action tendencies. Analyses of the means suggest that collective action tendencies become stronger the more fellow group members "put their money where their mouth is." The authors discuss how their dual pathway model integrates and extends elements of current approaches to collective action.

Understanding Social Media Logic

Abstract: Over the past decade, social media platforms have penetrated deeply into the mech­anics of everyday life, affecting people's informal interactions, as well as institutional structures and professional routines. Far from being neutral platforms for everyone, social media have changed the conditions and rules of social interaction. In this article, we examine the intricate dynamic between social media platforms, mass media, users, and social institutions by calling attention to social media logic—the norms, strategies, mechanisms, and economies—underpin­ning its dynamics. This logic will be considered in light of what has been identified as mass me­dia logic, which has helped spread the media's powerful discourse outside its institutional boundaries. Theorizing social media logic, we identify four grounding principles—programmabil­ity, popularity, connectivity, and datafication—and argue that these principles become increas­ingly entangled with mass media logic. The logic of social media, rooted in these grounding principles and strategies, is gradually invading all areas of public life. Besides print news and broadcasting, it also affects law and order, social activism, politics, and so forth. Therefore, its sustaining logic and widespread dissemination deserve to be scrutinized in detail in order to better understand its impact in various domains. Concentrating on the tactics and strategies at work in social media logic, we reassess the constellation of power relationships in which social practices unfold, raising questions such as: How does social media logic modify or enhance ex­isting mass media logic? And how is this new media logic exported beyond the boundaries of (social or mass) media proper? The underlying principles, tactics, and strategies may be relat­ively simple to identify, but it is much harder to map the complex connections between plat­forms that distribute this logic: users that employ them, technologies that drive them, economic structures that scaffold them, and institutional bodies that incorporate them.

Motivating Individuals and Groups at Work: A Social Identity Perspective on Leadership and Group Performance

Abstract: We argue that additional understanding of work motivation can be gained by incorporating current insights concerning self-categorization and social identity processes and by examining the way in which these processes influence the motivation and behavior of individuals and groups at work. This theoretical perspective that focuses on the conditions determining different self-definitions allows us to show how individual and group processes interact to determine work motivation. To illustrate the added value of this approach, we develop some specific propositions concerning motivational processes underpinning leadership and group performance.

A Tutorial on Regularized Partial Correlation Networks

Abstract: Recent years have seen an emergence of network modeling applied to moods, attitudes, and problems in the realm of psychology. In this framework, psychological variables are understood to directly affect each other rather than being caused by an unobserved latent entity. In this tutorial, we introduce the reader to estimating the most popular network model for psychological data: the partial correlation network. We describe how regularization techniques can be used to efficiently estimate a parsimonious and interpretable network structure in psychological data. We show how to perform these analyses in R and demonstrate the method in an empirical example on post-traumatic stress disorder data. In addition, we discuss the effect of the hyperparameter that needs to be manually set by the researcher, how to handle non-normal data, how to determine the required sample size for a network analysis, and provide a checklist with potential solutions for problems that can arise when estimating regularized partial correlation networks.