Weidong Li’s research while affiliated with Huazhong University of Science and Technology and other places

The ubiquitous monitoring and collection capabilities of the IoE, as well as its innovative scenarios, have led to changes in the content and type of personal data. Personal data sensitivity, as a standard for measuring privacy attitudes, can provide a reference for the design and improvement of privacy systems. This study aims to evaluate individuals’ personal data sensitivity in the IoE context, to better understand individuals’ current privacy attitudes. This study uses a questionnaire survey to study personal data sensitivity and the antecedents affecting personal data sensitivity among 1921 Chinese citizens. Research suggests that, within the spectrum of 41 personal data categories, identifiers such as ID numbers and home addresses are deemed highly sensitive. Furthermore, within the IoE context, emerging types of personal data, including behavioural and facial recognition data, also demonstrate significant sensitivity. With respect to sensitivity levels, personal data can be categorized into four tiers: very highly sensitive data, highly sensitive data, medium sensitive data, and low sensitive data. The study also finds that perceived privacy risks, privacy concerns, and social influences have a significant impact on personal data sensitivity, and there are differences in public perception of personal data sensitivity among different genders, ages, and educational levels.

This study investigates the complex relationship between internet use and citizen political participation, emphasizing the mediating role of social networks. Using cross-sectional data from the 2021 Chinese Social Survey (CSS), we classify political participation into government-led and citizen-led activities and internet use into informational, entertainment-oriented, and service-oriented types. Overall, our findings reveal a positive correlation between internet use and both citizen-led participation and government-led participation (excluding voting), with a stronger association observed in the former. From a categorical perspective, informational and service-oriented internet use significantly influences all types of political participation, while entertainment-oriented use shows no significant correlation. Additionally, social networks mediate the relationship between internet use and political participation. Service-oriented internet use is more dependent on social networks to connect with political participation compared to information-oriented internet use. This study contributes to the ongoing debate on the impact of digital media on civic engagement by providing nuanced insights into how specific internet activities and social networks shape political participation in China.

Personal physiological data is the digital representation of physical features that identify individuals in the Internet of Everything environment. Such data includes characteristics of uniqueness, identification, replicability, irreversibility of damage, and relevance of information, and this data can be collected, shared, and used in a wide range of applications. As facial recognition technology has become prevalent and smarter over time, facial data associated with critical personal information poses a potential security and privacy risk of being leaked in the Internet of Everything application platform. However, current research has not identified a systematic and effective method for identifying these risks. Thus, in this study, we adopted the fault tree analysis method to identify risks. Based on the risks identified, we then listed intermediate events and basic events according to the causal logic, and drew a complete fault tree diagram of facial data breaches. The study determined that personal factors, data management and supervision absence are the three intermediate events. Furthermore, the lack of laws and regulations and the immaturity of facial recognition technology are the two major basic events leading to facial data breaches. We anticipate that this study will explain the manageability and traceability of personal physiological data during its lifecycle. In addition, this study contributes to an understanding of what risks physiological data faces in order to inform individuals of how to manage their data carefully and to guide management parties on how to formulate robust policies and regulations that can ensure data security.

Purpose The Chinese government hopes to achieve the goal of benefiting citizens by building a National Integrated Online Government Service Platform (NIOGSP). However, citizens' low adoption of the platform makes it difficult for the government to achieve its goal. Research on the influencing factors of citizen adoption of NIOGSP can help the government fully understand the concerns and needs of its citizens and take targeted measures to increase citizen adoption. Design/methodology/approach First, this research builds a model of the citizen adoption process, including attention, retention and motivation, based on an observational learning model. Next, research variables are determined based on social cognitive theory, literature review and real-world needs. Finally, based on the questionnaire survey and structural equation model, the influencing factors of each stage of the citizen adoption process model are studied and the relationship between the three stages of the model is verified. Findings Results show that perceived usefulness (PU) and self-efficacy (SE) positively affect attention. SE positively affects retention, while perceived privacy (PP) negatively affects retention. PU, social influence, PP and anxiety positively affect motivation. Originality/value The conclusion of this study can provide reference for governments in various countries to establish and improve online one-stop government. In addition, this study verifies the citizen adoption process model and finds that there is no obvious causal relationship between attention and retention, but both have positive effects on motivation.