Two new papers out!

Paper in Personality and Social Psychology Bulletin

What is the paper about? (no, this is not just the abstract)

This study, based on the iSHAIB dataset (N = 133), investigates the connection between daily social interactions and changes in depressive symptoms using event-contingent experience sampling over three 21-day periods. While there are weak between-person effects for the quantity and perceived warmth of interactions, a significant and robust finding is the impact of overwarming—a novel construct reflecting the self-perceived difference in interpersonal warmth between oneself and interaction partners. The research underscores the crucial role that qualitative aspects of social interactions may have in influencing the progression of depressive symptoms.

Elmer, T., Ram, N., Gloster, A. T., & Bringmann, L. F. (2023). Studying Daily Social Interaction Quantity and Quality in Relation to Depression Change: A Multi-Phase Experience Sampling Study. Personality and Social Psychology Bulletin, 0(0). doi

Paper in EPJ Data Science

What is the paper about?

This paper delves into the maturation process of Computational Social Science (CSS), drawing an analogy to the exploratory phase of puberty in individuals. It emphasizes the necessity for CSS to harmonize its practices with those of neighboring disciplines, advocating for scientific rigor and a nuanced identity. Critically, the paper addresses reluctance in CSS to adopt robust scientific practices, particularly seen in an overreliance on passively collected data without validating its accuracy. The argument posits that CSS should blend passive and active measurement practices to leverage their respective strengths. Furthermore, the paper suggests integrating insights from established disciplines, proposing ten recommendations for CSS to evolve as a mature interdisciplinary field.

Elmer, T. Computational social science is growing up: why puberty consists of embracing measurement validation, theory development, and open science practices. EPJ Data Science. 12, 58 (2023). doi

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