A second-order adaptive network model for emotion regulation in addictive social media behaviour. (December 2021)

• Record Type: Journal Article
• Authors: Fokker, Elisabeth; Zong, Xinran; Treur, Jan
• Is Part Of: Cognitive systems research. Volume 70(2021)
• Page Start: 52
• Page End: 62
• Publication Date: 2021-12
• Subjects: Second-order adaptive; Cognition -- Periodicals; Cognitive engineering (System design) -- Periodicals; Artificial intelligence -- Periodicals; 153.05
• DOI: 10.1016/j.cogsys.2021.07.006
• Languages: English
• ISSNs: 1389-0417

Abstract

Abstract: Social media addiction has spread rapidly among young people in recent years. Individuals with social media addiction are more likely to avoid and suppress negative emotions instead of reappraising these emotions, which can cause psychological and even physical harm. This study presents a second-order adaptive mental network model to simulate the process of emotion regulation in social media addicts and the impacts of stress and therapy in this process. This network model can use three types of emotion regulation strategies: suppression, avoidance (by escaping to social media), and reappraisal. Using this model, two scenarios for a person with social media addiction are compared: with and without therapy. It is found that if therapy successfully improves the regulation by reappraisal, the use of suppression and avoidance can be reduced. Characteristics of this model were tuned by simulated annealing, using data points estimated from psychological literature, indicating that the model matches well with empirical information. The presented mental network model may also be used for other types of addictions which involve avoidance of emotions, such as alcohol abuse and game addiction.