[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.
[1] JOURARD S M, LASAKOW P. Some factors in self-disclosure[J]. Journal of abnormal & social psychology, 1958, 56(1):91-98.
[2] 搜狐网. LinkedIn遭黑客攻击,约1.59亿用户数据被窃[EB/OL].[2021-01-14]. https://m.sohu.com/a/292645813_557054.
[3] 百度百科.剑桥分析丑闻[EB/OL].[2021-01-14]. https://baike.baidu.com/item/%E5%89%91%E6%A1%A5%E5%88%86%E6%9E%90%E4%B8%91%E9%97%BB/49935337?fr=aladdin.
[4] KRASNOVA H, KOLESNIKOVA E, GVNTHER O. Leveraging trust and privacy concerns in online social networks:an empirical study[C]//18th European conference on information systems. Illinois:AIS elibrary, 2010.
[5] 郭海玲,马红雨,许泽辉.社会化媒体用户信息披露意愿影响模型构建与实证-以微信用户为例[J].图书情报工作,2019,63(15):111-120.
[6] DINEV T, HART P. Internet privacy concerns and their antecedents-measurement validity and a regression model[J]. Behaviour & information technology, 2004,23(6):413-422.
[7] 朱侯,王可,严芷君,等.基于隐私计算理论的SNS用户隐私悖论现象研究[J].情报杂志,2017,36(2):134-139.
[8] 张星,陈星,侯德林.在线健康信息披露意愿的影响因素研究:一个集成计划行为理论与隐私计算的模型[J].情报资料工作,2016(1):48-53.
[9] 王瑜超.在线医疗社区用户健康隐私信息披露意愿的影响因素研究[J].信息资源管理学报,2018,8(1):93-103.
[10] XU H, TEO H, TAN B C Y, et al. The role of push-pull technology in privacy calculus:the case of location-based services[J]. Journal of management information systems, 2010,26(3):135-174.
[11] 李征仁.移动互联网环境下用户隐私关注的影响因素及隐私信息扩散规律研究[D].北京:北京邮电大学,2014.
[12] 刘百灵,夏惠敏,李延晖.移动购物用户信息披露意愿影响因素的实证研究-基于公平理论和理性行为理论视角[J].情报理论与实践,2017,40(5):87-93.
[13] 李裕广.在线医疗社区患者医疗信息共享意愿影响因素研究[D].哈尔滨:哈尔滨工业大学,2015.
[14] ZLATOLAS N, WELZER T, HÖLBL M, et al. A model of perception of privacy, trust, and self-disclosure on online social networks[J]. Entropy, 2019,21(8):772-789.
[15] KO H, CHEN T. Understanding the continuous self-disclosure of bloggers from the cost-benefit perspective[C]//Proceedings of the 2nd conference on human system interactions. New York:IEEE Press, 2009.
[16] LOIACONO E T. Self-disclosure behavior on social networking web sites[J]. International journal of electronic commerce, 2015,19(2):66-94.
[17] 姜又琦.在线医疗网站用户个人健康信息披露意愿影响因素研究[D].武汉:武汉大学,2017.
[18] ZIMMER J C, ARSAL R, AL-MARZOUQ M, et al. Knowing your customers:using a reciprocal relationship to enhance voluntary information disclosure[J]. Decision support systems, 2010,48(2):395-406.
[19] PREMAZZI K, CASTALDO S, GROSSO M, et al. Customer information sharing with e-vendors:the roles of incentives and trust[J]. International journal of electronic commerce, 2014,14(3):63-91.
[20] STERN T, SALB D. Examining online social network use and its effect on the use of privacy settings and profile disclosure[J]. Bulletin of science technology & society, 2015,35(1):25-34.
[21] KIM E, LEE J, SUNG Y, et al. Predicting selfie-posting behavior on social networking sites:an extension of theory of planned behavior[J]. Computers in human behavior, 2016,62(9):116-123.
[22] BANSAL G, ZAHEDI F M, GEFEN D. The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online[J]. Decision support systems, 2010,49(2):138-150.
[23] ADAMS A, SASSE M A. Privacy in multimedia communications:protecting users, not just data[M]. London:Springer, 2001.
[24] CUNNINGHAM J S, MASOODIAN M, ADAMS A. Privacy issues for online personal photograph collections[J]. Journal of theoretical & applied electronic commerce research, 2010,5(2):26-40.
[25] JENNETT C, BROSTOFF S, MALHEIROS M, et al. Adding insult to injury:consumer experiences of being denied credit[J]. International journal of consumer studies, 2012, 36(5):549-555.
[26] 石文华,陈楠,张绮.关系类型和信息类型对社交网络用户转发意愿的影响研究[J].制度经济学研究,2016(4):162-180.
[27] 万晓榆,杨腾,袁野,等.微博信息情绪类型对用户分享意愿的影响研究[J].情报科学,2019,37(8):97-107.
[28] 侯敏.用户社交网络平台信息分享行为研究-以上海市大学生微博使用为例[J].中国报业,2020(10):16-17.
[29] JIN L, LONG X, JOSHI J B D. Towards understanding residential privacy by analyzing users' activities in foursquare[C]//Proceedings of the 2012 ACM workshop on building analysis datasets and gathering experience returns for security. New York:ACM Press, 2012.
[30] 杨世宏,陈堂发,张睿.隐私风险估算框架下用户位置信息敏感性认知[J].兰州大学学报(社会科学版),2019,47(4):8-16.
[31] 中国网信网.第47次《中国互联网络发展状况统计报告》[R/OL].[2021-03-03]. http://www.cac.gov.cn/2021-02/03/c_1613923423079314.htm.
[32] TSAI J Y, KELLEY P, DRIELSMA P, et al. Who's viewed you? The impact of feedback in a mobile location-sharing application[C]//Proceedings of the SIGCHI conference on human factors in computing systems.New York:ACM Press,2009.
[33] SADEH N, HONG J, CRANOR L, et al. Understanding and capturing people's privacy policies in a mobile social networking application[J]. Personal and ubiquitous computing, 2009,13(6):401-412.
[34] 新浪财经.微博发布2020年第三季度财报[R/OL].[2021-03-03]. https://finance.sina.com.cn/stock/usstock/c/2020-12-28/doc-iiznezxs9422515.shtml.
[35] 新浪微博数据中心.2018年微博用户发展报告[EB/OL].[2021-03-03]. https://data.weibo.com/report/reportDetail.
[36] 中华人民共和国民政部. 2020年中华人民共和国行政区划代码[EB/OL].[2021-03-03]. http://www.mca.gov.cn/article/sj/xzqh/2020/.
[37] STRANO M M. User descriptions and interpretations of self-presentation through facebook profile images[J]. Journal of psychosocial research on cyberspace,2008,2(2):1-10.
[38] 臧国全,周晓倩.隐私关注困扰下用户持续使用社交网络的动机解析[J].情报理论与实践,2020,43(3):71-77.
[39] 杨嫚,温秀妍.隐私保护意愿的中介效应:隐私关注、隐私保护自我效能感与精准广告回避[J].新闻界,2020(7):41-52.
[40] 卢家银,白洁.中国青年的网络隐私忧虑及其影响因素研究——基于对1599名共青团员的实证调查[J].新闻记者,2021(2):69-79.
[41] 吴标兵,许和隆,张宇.中国公众隐私敏感度实证研究[J].南京邮电大学学报(社会科学版),2015,17(3):82-90.
[42] PREOTIUC-PIETRO D, COHN T. Mining user behaviors:a study of check-in patterns in location based social networks[C]//Proceedings of the 5th annual ACM web science conference. New York:ACM press, 2013.
[43] FIRE M, KAGAN D ELISHAR A, et al. Social privacy protector-protecting users' privacy in social networks[C]//The second international conference on social eco-informatics. Venice:IARIA XPS press,2012.
