自我表露
相关性(法律)
独创性
构造(python库)
结构方程建模
心理学
社会化媒体
心理干预
信息共享
社会心理学
计算机科学
政治学
机器学习
精神科
创造力
万维网
法学
程序设计语言
作者
Nik Thompson,Jack Brindley
出处
期刊:Information Technology & People
[Emerald Publishing Limited]
日期:2020-07-14
卷期号:34 (3): 999-1017
被引量:17
标识
DOI:10.1108/itp-04-2019-0197
摘要
Purpose This paper contrasts the determinants of online disclosures about self and others in social media. Design/methodology/approach Data from 216 respondents were collected through an online survey. The formal research model was tested with covariance based structural equation modeling. Findings The determinants of online disclosures vary whether the subject is self or others. Social networking site (SNS) users who self-disclose are also more likely to share information about others. Furthermore, there are significant gender effects in the influences of disclosure as revealed by multi-group SEM. Research limitations/implications Future research models should incorporate the construct of disclosure about others and examine the intertwining of different types of disclosure on SNS. Future work should include behavioral measures, as this study relied on self-report measures. Practical implications The current understanding of information sharing does not accommodate different forms of disclosure. Employers or systems administrators concerned about data sharing may need to tailor interventions to the subject of the disclosure. Furthermore, the significant gender differences in determinants of disclosure suggest that this should be considered in practical applications. Originality/value Disclosure about others has not been examined in prior work. This study contributes by offering empirical data on the contrasting determinants of disclosure as well as gender differences. It improves the understanding of online information sharing, a topic of particular relevance in today's information oriented society.
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