Understanding Chinese Internet users' information sensitivity in big data and artificial intelligence era

Abstract

AbstractThe online environment has evolved with the development of emerging information technologies. In response to rising voices discussing the boundaries of collecting and using user data on platforms, this study explored Chinese Internet users' information sensitivity as an indicator of data classification governance. This study employed a two‐stage research approach. First, 60 types of information that users disclose to Internet platforms in the era of big data and artificial intelligence (AI) were identified. Biometric identification, travel records, preference, trace information, and other information reflecting the characteristics of network collection in the era of big data and AI were also included. Second, based on 397 questionnaires, the information categories were clustered into five groups: less‐sensitive social attributes, consumption traces, individual action details, potential risk information, and health and social sensitivity. Of the total disclosed information types, 61.7% were perceived as highly sensitive by Chinese users in the current Internet environment; the higher the sensitivity of the information, the less likely users were to disclose it and use the online platform. Moreover, newly added information types have a high sensitivity. These findings provide insights into the policy design and governance of Internet platform data collection and usage practices in the era of big data and AI.