社交网络数据隐私保护：溯源、技术、政策、展望

doi:10.13998/j.cnki.issn1002-1248.24-0242

摘要/Abstract

摘要： [目的/意义]社交网络数据隐私保护是总体国家安全观的重要组成部分,数字经济时代,如何发挥数据要素作用的同时保护数据隐私安全成为学界热点。本研究通过分析国内外研究现状及局限性,以期为后续研究提供借鉴。[方法/过程]首先,采用文献调研法,从不同领域和时代视角归纳社交网络数据隐私保护发展历程;其次,通过内容分析法,从隐私泄露、隐私保护手段和隐私度量3个维度进行主题内容挖掘;最后,基于信息生态框架,探究如何使保护体系可持续健康发展。[结果/结论]社交网络数据隐私保护研究涉及多学科领域和多数据生命周期,根据研究内容,可分为隐私泄露、隐私保护技术、隐私保护管理和隐私度量4部分。为适应日渐复杂的现实环境和数智化的时代趋势,势必要在技术优化、法律完善、平台监管和用户参与的基础上,构建四位一体的社交网络数据隐私保护生态。

关键词: 社交网络, 数据隐私, 隐私泄露, 隐私保护技术, 隐私管理, 隐私度量

Abstract: [Purpose/Significance] The advent of the Internet and the subsequent evolution of new technologies and applications, such as big data and artificial intelligence, have spurred the exponential growth of a new generation of technologies. China has entered the era of data-driven digital intelligence, with social network data privacy protection playing a crucial role in the country's comprehensive security strategy. By studying the evolution of this field, we gain insights into how to protect personal information, foster the healthy development of social platforms, and facilitate the responsible circulation of data elements. Compared to previous studies, this paper offers a broader range of perspectives, exploring the main directions and roles of each element of privacy protection with the information ecology theory, and more comprehensive research content, and combining causes, technologies, management and metrics.We propose an ecological framework for social network data privacy protection, based on a thorough overview of the subject matter. This framework serves as a reference point for the evolving landscape of privacy protection practices. [Method/Process] This study uses two different approaches: literature review and content analysis. The former is utilized to identify and categorize literature related to CNKI and WOS, while the latter is employed to visually analyze and interpret this corpus using Citespace. This study provides a systematic review of data privacy protection in social networks in four dimensions: privacy protection triggers, privacy leakage, privacy protection technology, and privacy protection management. The review is based on the visualization and analysis of both Chinese and international literature. Furthermore, we present our perspective on information ecology, integrating analyses of research themes and limitations for each information topic. We also explore strategies to promote the sustainable and healthy development of behaviors related to data privacy protection in social networks. [Results/Conclusions] Interdisciplinary exchange on data privacy protection in social networks is essential to advance the digital intelligence era. Relying solely on isolated methods of privacy protection is insufficient in the face of an increasingly complex application environment and the trends towards digitalization and intelligence. It is therefore necessary to establish a comprehensive privacy protection system that integrates technical optimization, legal improvements, platform regulations, and user engagement. Specifically, from a technical perspective, it is essential to leverage a variety of technologies to develop solutions for privacy protection. From a legal perspective, there is a need to refine the content, standardize the adjudication process, and strengthen supervision and sanctions. At the platform level, optimizing the content of privacy policies and ensuring their effectiveness are crucial. Finally, at the user level, it is essential to raise awareness of privacy protection and to enhance privacy protection capabilities. Moreover, it is crutial to examine the inherent relationship between each entity and the methods of protection. A key limitation of this paper is the lack of an in-depth analysis of the interaction mechanisms between stakeholders within the ecological framework of social network data privacy protection. Future iterations will address this by incorporating a background on the complex information environment and conducting a more in-depth analysis of the interaction mechanisms.

Key words: social networks, data privacy, privacy breaches, privacy-protection technologies, privacy management, privacy metrics

中图分类号: G203

杨瑞仙, 李航毅, 孙倬. 社交网络数据隐私保护：溯源、技术、政策、展望[J]. 农业图书情报学报, 2024, 36(4): 4-20.

YANG Ruixian, LI Hangyi, SUN Zhuo. Privacy Protection of Social Network Data: Traceability, Technology, Policy and Perspectives[J]. Journal of Library and Information Science in Agriculture, 2024, 36(4): 4-20.

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