ArticleFrontiers in public health2022
Prediction model of interaction anxiousness based on Weibo data.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 6 citations in OpenAlex.
- Mental Health Risk Detection From Social Media Text Data: A Scoping Review of the Machine Learning Research Landscape.PsyCh journal · 2026Article
- Challenges and countermeasures of China's research on "sports promoting adolescent socialization"-data mining based on Weibo and CNKI.Frontiers in psychology · 2023Review
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2 authors at 2 institutions in 1 country.
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Abstract
Adolescents who face social distress in real life are often accompanied by interaction anxiousness. To avoid direct social activities, they prefer to indulge in social networks to satisfy their psychological needs for interpersonal communication. Sina Weibo, China's leading social media platform, has a markedly young user base. It provides a rich sample of adolescents with interaction anxiousness and conditions for real-time monitoring. In this study, various word categories, such as perception of spatial distance and positional relationships, morality, and emotion, showed a significant relationship with interaction anxiousness. Furthermore, prediction models were established based on the original Weibo data of 839 active Sina Weibo users through a variety of machine learning algorithms to predict the scores of users' interaction anxiousness. The results showed that the performance of the prediction model established by the fully connected neural network was the best, and both criterion validity and split-half reliability were good (
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