大数据时代隐私披露意愿的统计分析

Statistical Analysis of Factors Influencing Willingness to Disclose Privacy in the Era of Big Data

随着大数据时代的发展,APP中频繁发生的隐私泄露问题影响用户的隐私披露意愿,而用户隐私披露意愿又与APP发展有关。为了帮助APP更好发展,本文将对APP用户隐私披露意愿的情况和影响因素进行研究,为其提供理论依据。首先,使用Python对用户隐私披露情况进行可视化,发现多数用户认为APP过度收集个人信息。其次,基于隐私计算理论和沟通隐私管理理论,从用户情感和行为角度确定影响因素,设计收集问卷,构建结构方程,得到感知有用性、习惯性、社交媒体信任性对披露意愿有正向影响,感知风险性、隐私控制性、隐私关注性有负向影响。最后,建立随机森林模型探究影响用户隐私披露意愿的核心因素,以准确率为标准,感知风险性和隐私关注性是核心因素;以GINI指数为标准,习惯性和感知有用性是核心因素。

With the development of the big data era, the frequent privacy leakage problems in APPs affect users’ willingness to disclose their privacy, which in turn is related to APP development. To help APPs develop better, we study the situation and influencing factors of APP users’ willingness to disclose privacy to provide a theoretical basis for it. First, we use Python to visualize user privacy disclosure and find that most users believe that the app over-collects personal information. Secondly, based on privacy computing theory and communication privacy management theory, we identify the influencing factors from the perspective of users’ emotions and behaviors, design a collection questionnaire, construct structural equations, and obtain that perceived usefulness, habituation, and social media trust have positive effects on disclosure intention, and perceived riskiness, privacy control, and privacy concern have negative effects. Finally, we build a random forest model to explore the core factors, with perceived riskiness and privacy concern as the core factors in terms of accuracy, and habituation and perceived usefulness as it in terms of GINI index.