Huang, Lei, Jingyi Zhou, Jiecong Lin, & Shengli Deng (2021, November). View analysis of personal information leakage and privacy protection in big data era—based on Q method. Aslib Journal of Information Management. (ePub in advance of print). (Link: https://doi.org/10.1108/AJIM-05-2021-0144)

Abstract: Purpose: In the era of big data, people are more likely to pay attention to privacy protection with facing the risk of personal information leakage while enjoying the convenience brought by big data technology. Furthermore, people’s views on personal information leakage and privacy protection are varied, playing an important role in the legal process of personal information protection. Therefore, this paper aims to propose a semi-qualitative method based framework to reveal the subjective patterns about information leakage and privacy protection and further provide practical implications for interested party. Design/methodology/approach: Q method is a semi-qualitative methodology which is designed for identifying typologies of perspectives. In order to have a comprehensive understanding of users’ viewpoints, this study incorporates LDA & TextRank method and other information extraction technologies to capture the statements from large-scale literature, app reviews, typical cases and survey interviews, which could be regarded as the resource of the viewpoints. Findings: By adopting the Q method that aims for studying subjective thought patterns to identify users’ potential views, the authors have identified three categories of stakeholders’ subjectivities: macro-policy sensitive, trade-offs and personal information sensitive, each of which perceives different risk and affordance of information leakage and importance and urgency of privacy protection. All of the subjectivities of the respondents reflect the awareness of the issue of information leakage, that is, the interested parties like social network sites are unable to protect their full personal information, while reflecting varied resistance and susceptibility of disclosing personal information for big data technology applications. Originality/value: The findings of this study provide an overview of the subjective patterns on the information leakage issue. Being the first to incorporate the Q method to study the views of personal information leakage and privacy protection, the research not only broadens the application field of the Q method but also enriches the research methods for personal information protection. Besides, the proposed LDA & TextRank method in this paper alleviates the limitation of statements resource in the Q method

Lei Huang is in the Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong.

Leave a Reply

Please log in using one of these methods to post your comment:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.