图书情报工作 ›› 2021, Vol. 65 ›› Issue (16): 90-97.DOI: 10.13266/j.issn.0252-3116.2021.16.010

• 情报研究 • 上一篇    下一篇

社交网络用户自我披露意愿研究——以新浪微博为例

臧国全1,2, 孔小换1, 张凯亮3, 于政杰1   

  1. 1 郑州大学信息管理学院 郑州 450001;
    2 郑州市数据科学研究中心 郑州 450001;
    3 郑州大学政治与公共管理学院 郑州 450001
  • 收稿日期:2021-03-29 修回日期:2021-06-15 出版日期:2021-08-20 发布日期:2021-08-20
  • 通讯作者: 张凯亮(ORCID:0000-0003-0454-0525),博士研究生,通讯作者,E-mail:779015223@qq.com。
  • 作者简介:臧国全(ORCID:0000-0002-9606-6455),院长,教授,博士生导师;孔小换(ORCID:0000-0001-9858-016X),硕士研究生;于政杰(ORCID:0000-0003-2707-0669),硕士研究生。
  • 基金资助:
    本文系国家自然科学基金项目"数字保存的风险型元数据与风险监控研究"(项目编号:71673255)研究成果之一。

Research on Social Network Users' Willingness to Self-Disclosure——A Case of Sina Microblog

Zang Guoquan1,2, Kong Xiaohuan1, Zhang Kailiang3, Yu Zhengjie1   

  1. 1 School of Information Management, Zhengzhou University, Zhengzhou 450001;
    2 Research Institute of Data Science, Zhengzhou City, Zhengzhou 450001;
    3 School of Politics and Public Administration, Zhengzhou University, Zhengzhou 450001
  • Received:2021-03-29 Revised:2021-06-15 Online:2021-08-20 Published:2021-08-20

摘要: [目的/意义] 社交网络用户自我披露对以用户生成内容为业务基础的社交网络具有战略意义,而用户生成内容的数量和质量取决于用户自我披露意愿。因此,研究社交网络用户自我披露意愿及其影响因素,为社交网络平台制定隐私政策、提升用户自我披露水平提供参考,促进社交网络平台的健康快速发展。[方法/过程] 参考已有研究框架,构建社交网络用户自我披露意愿的研究模型。选择新浪微博作为社交网络平台代表,采用Python爬虫方法获取用户微博数据,据此分析用户自我披露意愿。[结果/结论] 微博内容的语义、位置标签和数据权限均影响用户自我披露意愿,隐藏位置标签和设置数据权限等操作会显著提高用户自我披露意愿。社交网络用户自我披露意愿是一种个人特质,受性别、年龄、学历等人口统计学因素影响。

关键词: 社交网络, 自我披露, 披露意愿, 新浪微博

Abstract: [Purpose/significance] Users' self-disclosure is of strategic significance to social network platforms based on user-generated content, and the quantity and quality of user-generated content depend on the user's willingness to self-disclosure. Therefore, the study of users' willingness to self-disclosure and its influencing factors can provide reference for social network platforms to formulate privacy policies and encourage users to disclose personal information, to promote the development of social networks platforms.[Method/process] Based on the existing research framework, a research model of social network users' self-disclosure willingness was constructed. This study took Sina microblog as an example, and adopted python crawler method to obtain users' personal data to analyzed users' willingness to self-disclosure.[Result/conclusion] Semantic content, location tags and data permission of microblog all affect users' willingness to self-disclosure. Hiding location tags and setting data permission can significantly improve users' willingness to self-disclosure. Social network users' willingness to self-disclosure is a kind of personal characteristics, which is affected by demographic factors, such as gender, age and education background of users.

Key words: social network, self-disclosure, disclosure willingness, Sina microblog

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