원문정보
초록
영어
Moving beyond existing assumptions that regard personal information as fixed and practices that focus solely on its collection and use, advances in data processing methods have enabled the construction of digital entities using digitally captured personal data. From the perspective of the datafication of privacy, we attempt to identify individuals’ digital data across different contexts and examine how data processing levels and the identifiability of a person are associated. To this end, we collected users’ perceptions of personal data in social media and online shopping contexts and examined the relationships between data processing levels―measured by human- machine-generated and changeability characteristics―and the identifiability of personal data. Based on an exploratory examination of various data types in two contexts, we suggest new personal information categories that embrace the notion of data processing.
목차
Ⅰ. Introduction
Ⅱ. Literature Review: Identifying Individuals by their Personal Information
Ⅲ. Theoretical Background
3.1. The Datafication of Privacy
3.2. Processed Personal Data Characteristics
3.3. Human-Machine-Generated Characteristics
3.4. Changeability Characteristics
Ⅳ. Method
4.1. Context Selection
4.2. Measurements
4.3. Data Collection
Ⅴ. Analysis Results
5.1. Associations between Data Processing and Identifiability
5.2. Classifying Data Types by Associationwith Multiple Data Characteristics
Ⅵ. Discussion
Ⅶ. Implications
7.1. Theoretical Implications
7.2. Practical Implications
7.3. Limitations and Future Work
Ⅷ. Conclusions
Acknowledgements