灵敏度(控制系统)
社会化媒体
萧条(经济学)
心理学
社会心理学
计算机科学
经济
万维网
工程类
电子工程
宏观经济学
作者
Dan-Mircea Mirea,Judith N. Mildner,Seán Kelley,Claire M. Gillan,Erik C. Nook,Yael Niv
标识
DOI:10.31234/osf.io/4ynbc
摘要
The interaction between social media use and mental health is of great public health concern. Studies so far, largely employing self-reported measures of social media use, have produced inconclusive evidence regarding the impact of social media on mental health. Focusing on objective behavioral markers and the psychological mechanisms underlying how users interact with social media platforms could be key to greater insight on this topic. Here we use Twitter data to study how depression modulates a central behavioral process on social media: the response to the social rewards (e.g. likes, shares, views) users receive when they post. Reinforcement learning theory predicts that social media rewards will reinforce posting behavior, such that receiving more likes will lead to posting more frequently and spending more time on the platform. However, laboratory tasks often show blunted reinforcement learning in depression, suggesting a potential attenuation of the effects of social rewards on posting behavior. Across 3 datasets with varied measures of depression and data collection strategies (over 17 million tweets from 7744 users in total, including a pre-registered replication), we consistently found that depression was associated with a larger reinforcing effect of likes on posting on the next day. In other words, users with depression showed heightened sensitivity to social media rewards, in contrast to findings from laboratory-based tasks. These results identify a psychological mechanism that may link social media use to poor mental health, and underscore the importance of testing the generalizability of in-lab computational psychiatry findings to real-world environments.
科研通智能强力驱动
Strongly Powered by AbleSci AI