Qinghua Yang, Andrew M. Ledbetter, J. Zhuang, A. Richards
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引用次数: 0
Abstract
Despite the common use of social media to discuss health issues, little is known about how features of user-generated content influence users’ health outcomes. To address this gap, we longitudinally studied large-scale conversations on the subreddit r/loseit, an online weight loss community, by computationally analyzing the themes and sentiment of users’ posts and examining their associations with users’ self-reported weight loss. Our study identified 28 distinct topics on r/loseit, many of which significantly predicted post score and the number of responsive comments. We also found that the post score was predicted by positive sentiments, whereas the number of comments was predicted by negative sentiments. Further, users’ posts on the topic of goal setting significantly predicted their self-reported weight loss, and such association was amplified when the post score and the number of comments are high. Our findings have important theoretical and practical implications for the relationship between interactions in online communities and health outcomes.
期刊介绍:
ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.