Positive and Negative Emotions Predict Weight Loss Intentions and Behaviors beyond Theory of Planned Behavior Constructs

Acknowledgements: This study was funded by the ScienceCampus Tuebingen (TP7.1) awarded to Devin G. Ray and Kai Sassenberg.Peer reviewedPostprin

Just do it or do it right?: How regulatory mode relates to perceived responsibility and opportunity in collaborations

In many contexts, people collaborate with others to complete tasks. Collaboration provides opportunities toachieve goals (e.g., to combine expertise and split workload), but also responsibilities to ensure that things go well (e.g., that work assignments are appropriate and that different contributions are taken into account). Successful collaboration likely requires both types of individuals—those who consider the opportunities and those who recognize the responsibilities. But how can these people be identified? The present research studied the role of people’s regulatory mode as predisposing them to focus on the opportunity or responsibility of collaboration. Going beyond prior work, we predicted that a locomotion mode to “move on” towards desired outcomes would primarily be associated with perceiving collaboration as an opportunity to do so; in contrast, an assessment mode to evaluate how to “do things right” should be linked to perceiving collaboration primarily as a responsibility. Seven studies (N = 1318) across multiple study contexts found meta-analytical evidence for the predicted relations (more so than for alternative relations). Accordingly, the way in which people typically regulate behavior towards desired end-states contributes to understanding how they likely perceive (and potentially engage in) collaborations with others.Social decision makin

A matter of focus: power-holders feel more responsible after adopting a cognitive other-focus, rather than a self-focus

Social decision makin

An Agent-Based Model of Collective Emotions in Online Communities

We develop a agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agents individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a superlinear feedback between the information field and the agent's arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities.Comment: European Physical Journal B (in press), version 2 with extended introduction, clarification