Digital technology and mental health: Chinese university students' perspectives on the impact of social media by Chi Zhang

“… # Methods We investigate the extent of this issue by looking at how Chinese social media platforms like WeChat, Weibo, and QQ impact students' mental health. To gain a comprehensive insight into students' perspectives, this study's sole methodology is qualitative semi-structured interviews. …”
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From ChatGPT to Sora: Analyzing Public Opinions and Attitudes on Generative Artificial Intelligence in Social Media by Wenyan Feng, Yuhang Li, Chunhao Ma, Lisai Yu

“…This study examines public opinions, emotional tendencies, and psychological linguistic characteristics associated with the launch of OpenAI’s ChatGPT and the advanced video generation model, Sora, by analyzing discussions on the Chinese social media platform Weibo. A total of 24,727 valid user-generated texts (1,762,296 words) were collected and analyzed using Python and its associated APIs. …”
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Social media usage and cyberbullying: the moderating role of tie strength by Jinru Ni, Hongyu Fu, Yajing Zhu, Zewen Li, Shuyi Wang, Haoran Su

“…The order of tie strength between users and the four platforms is as follows: WeChat > Bilibili > Weibo > Douyin. (2) Strong-tie social media platforms exhibited higher levels of users’social media engagement compared to those with weak ties. (3) Weak ties significantly moderated the relationship between social media usage and cyberbullying, whereas strong ties did not. …”
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GroupFound: An effective approach to detect suspicious accounts in online social networks by Bo Feng, Qiang Li, Xiaowen Pan, Jiahao Zhang, Dong Guo

“…We evaluate GroupFound on Sina Weibo dataset and find an appropriate threshold to identify suspicious accounts. …”
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Demonstration of Participation Networks in Urban Transport Policy of Public and Private Sectors through Social Media: The Case of Bike-Sharing Pricing Strategy in China by Qian Ye, Xiaohong Chen, Hua Zhang, Junjie Cai, Kaan Ozbay

“…Dataset on retweets from the Chinese Twitter-Sina Weibo is collected. Results reveal two types of important actors with unequal roles in terms of information diffusion: the “network root” and the “network bridge.” …”
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Depression Detection in Social Media: A Comprehensive Review of Machine Learning and Deep Learning Techniques by Waleed Bin Tahir, Shah Khalid, Sulaiman Almutairi, Mohammed Abohashrh, Sufyan Ali Memon, Jawad Khan

“…The rapidly growing world of social media sites such as Twitter, Reddit, Facebook, Instagram, and Weibo has provided new avenues for depression detection using Machine Learning (ML) as well as Deep Learning (DL), which analyze user behavior patterns and linguistic cues for more accurate detection of depression. …”
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