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The evolution and governance of online rumors during the public health emergency: taking COVID-19 pandemic related rumors as an example
Published in Jiuping Xu, Syed Ejaz Ahmed, Zongmin Li, Big Data and Information Theory, 2022
As the most popular platform in China, Sina Weibo has 511 million monthly active users and 224 million daily active users by September 2020. Different from the China Internet Joint Rumor Refuting Platform and Baidu Rumor Refuting Platform, Sina Weibo not only allows official accounts to publish rumor-refuting microblogs, but also allows people to repost, comment and give thumbs up, which can reflect the changes of public concerns based on content mining. Therefore, this paper took Sina Weibo as the data source, retrieves key words included ‘COVID-19’, ‘novel coronavirus’, ‘CoV’ and so on.
Public opinion on MOOCs: sentiment and content analyses of Chinese microblogging data
Published in Behaviour & Information Technology, 2022
Weibo (a Chinese microblogging platform) is one of the most widely used social networking sites in China. By the third quarter of 2016, Weibo had 297 million monthly active users and 132 million daily active users (Weibo Data Center 2016). Although often referred to as the Chinese version of Twitter, Weibo is more like an integration of Twitter, Facebook, and Medium. As Weerasekara (2018) noted, Weibo users interact much more with each other than Twitter users do. Approximately 80% of China’s university students are Weibo users and 42% are daily active users. In comparison, in the U.S. only approximately one third of students use Facebook and Twitter.
Research on the behaviour and law of quantity growth of followers based on WeChat official account
Published in Behaviour & Information Technology, 2021
Wenming Hou, Xiaoqiang Di, Jinqing Li, Li Cheng, Huamin Yang
With the advent of the Web 2.0 era (Sun et al. 2014), self-media has become an important source of information for a great number of people in recent years. Individuals, governments, media and businesses can have their own self-media accounts (Wang and Deng 2013). These accounts can provide a variety of life services including news, weather, entertainment, living expenses, etc. As the typical representative of its kind, the WCOA (Zhang and Li 2014) and Weibo (Chen, Han, and Wu 2013) are the most influential self-media in China. Up to the third quarter of 2017, the monthly active users of Weibo were 376 million (Center 2018). Compared with Weibo, WeChat had approximately 1 billion monthly active users (Center 2018). Such popularity makes the pattern of followers’ behaviour and the changing law of quantity in self-media become an object of interest (Cao et al. 2014; Lin et al. 2016). Recent evidence suggests that the ability of the self-media platform to disseminate information is closely related to its number and behaviour of followers (Zhang, Xu, and Li 2013; Cao et al. 2014). Surveys conducted by Jin, Jin, and Tang (2015) and Liao and Wang (2017) show that the number of followers significantly affects the forwarding amount and communication effect of Weibo. That is, more followers means more forwarding numbers, comments, and a better dissemination effect. From followers’ behaviour, Zhao et al. (2009) finds that there is a power-low relationship between followers’ reading behaviour and times in Weibo. Qu et al. (2011) studied the forwarding of emotion, opinions, situation updates, action-related categories and others of Weibo, and find the forwarding times of all these categories approximately follow the power-law distribution. Li (2013) also finds that the sharing number for hot topics follows a power-low distribution. For the law of the quantity change of followers, Lin et al. (2016) and Wu and Wang (2011) find that the number of followers approximated the power-law distribution over a period of time. Therefore, drawing on the analysis methods and theories of Weibo followers, we can study the behaviour patterns and the law of quantity change of WCOA followers.
Analysis of Factors Influencing We-Intention in Healthcare Applications Based on the AISAS Model
Published in International Journal of Human–Computer Interaction, 2023
Ming Yuan Ding, Wei-Tsong Wang
Since we did not intend to limit the types of the healthcare applications investigated, we collected data in order to ensure the number of valid questionnaires and a representative sample of the users of various kinds of healthcare applications. The population of this study is the healthcare application users in mainland China and Taiwan. The survey participants of this study were adult users of healthcare applications that were recruited from well-known social network platforms in mainland China and Taiwan. We presented the introduction of our research to some group members of healthcare applications on Weibo and WeChat platforms and invited them to fill out our online questionnaire. Weibo is a relationship-based social media platform that can be accessed through various computing devices, including traditional personal computers, laptop, and mobile phones. Weibo provides its users with functions that support instant sharing, dissemination and interaction of information in multimedia forms (e.g., text, pictures, and videos). According to Weibo’s official website, the number of daily active online Weibo users was 249 million in December 2021. Weibo is one of the largest social networking service providers in mainland China, and WeChat is the most popular free communication applications in China that provides instant messaging services. Through the above two platforms, we could obtain an adequate sample in mainland China that can meet the requirements of this study. In Taiwan, we used Facebook and PTT platforms to promote our survey and invited users of healthcare applications to fill out questionnaires. Facebook is one of the most popular social networking services in Taiwan, and PTT is the largest online platform that hosts lots of online communities of practices and online forums. We searched for discussion boards and/or online forums on those two platforms in Taiwan that were related to the subjects relevant to the research context of this study, such as “healthcare applications”, “fitness”, and “Strava.” We then presented an introduction of our research purpose and the criteria that our potential survey participants must fulfill in those discussion boards and/or online forums.