Abstract
Online health communities (OHCs) have emerged as dynamic platforms facilitating patient communication and knowledge exchange on health matters. While extant research underscores the emotional benefits accrued from engagement in OHCs, the precise quantification of how social support within these communities influences users’ emotional states remains an intricate challenge. In light of this, the primary objective of this study is to explore the influential mechanisms underlying the received social support on the emotional improvement of users in OHCs, while concurrently investigating the potential moderating effects posed by individuals’ health conditions and levels of community involvement. Leveraging authentic user interaction data harvested from an online diabetes community, this study employed deep learning models and natural language processing methods to gauge the magnitude of received social support and the variation of users’ emotional states. Subsequently, a multiple linear regression model was formulated to evaluate the effects of both informational and emotional support on users' emotional improvement. Empirical results reaffirm the pivotal role of both informational and emotional support in enhancing users’ emotional states, with emotional support emerging as particularly influential. Notably, prolonged disease duration amplifies the beneficent impact of social support on emotional enhancement. The research outcomes bear implications for ameliorating negative emotional experiences and effectively managing chronic diseases.
Published Version
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