Thought must be studied, observed, and understood.

Thought is the instrument through which human beings approach knowledge, relationship, culture, conflict, and the future itself. Yet our understanding of thought’s actual operation remains limited: how it forms images, defends conclusions, binds itself to emotion, divides people into opposing camps, and then tries to solve the very problems it has helped create. Thought Studies collects work that can make this process more visible, because understanding thought is not a narrow academic question; it is essential to the well-being and survival of our species.

  1. Imagined otherness fuels blatant dehumanization of outgroups
  2. Exploring the Relationship Between Need for Closure, Religious Ideology, and Identity Fusion
  3. Significant PaperOn Self-Deception in the Individual, in Groups, and in Society as a Whole
  4. Ideology: Psychological Similarities and Differences Across the Ideological Spectrum Reexamined
  5. Modeling the emergence of affective polarization in the social media society
  6. A Threat to Cohesion: Intragroup Affective Polarization in the Context of Intractable Intergroup Conflict
  7. Intergroup threat and affective polarization in a multi-party system
  8. “Be Nice or Leave Me Alone”: An Intergroup Perspective on Affective Polarization in Online Political Discussions
  9. Intergroup Hostility in the Public Sphere: Systematizing the Rising Concern for Affective Polarization Beyond Partisan Lines
  10. Identity concerns drive belief: The impact of partisan identity on the belief and dissemination of true and false news
  11. Intellectual humility as a tool to combat false beliefs: An individual‐based approach to belief revision
  12. Threats, Emotions, and Affective Polarization
  13. We love, they hate: Emotions in affective polarization and how partisans may use them
  14. What drives people to prefer health-related misinformation? The viewpoint of motivated reasoning
  15. Tracking politically motivated reasoning in the brain: the role of mentalizing, value-encoding, and error detection networks