Privacy Protection in Social Science Research
Possibilities and Impossibilities
Bibliographic Data
| ID | 12379436 |
|---|---|
| Authors | Jeremy J Albright, Jeremy Albright (0000-0001-5608-4838, corresponding author) |
| Year | 2011 |
| Volume | 44 |
| Issue | 4 |
| Pages | 777-782 |
| Publication date | 2011-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | PS Political Science & Politics (JOURNAL) |
| Journal identifiers | ISSN: 1049-0965 • E-ISSN: 1537-5935 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s1049096511001405 |
| OpenAlex | W2008032506 |
| Language | EN |
| Citations received | 1 |
| References cited | 20 |
The ubiquity of data in the twenty-first century provides unprecedented opportunities for social science research, but it also creates troubling possibilities for privacy violations. The emerging field of statistical disclosure control (SDC) studies how data collectors and analysts can find an optimal solution to balancing privacy protection and data utility. This article introduces SDC to readers in the applied political science research community and outlines its implications for analyzing individual-level data. The vocabulary of SDC is introduced and is followed with a discussion emphasizing just how easy it is to break almost any release of supposedly “anonymized” data. The article then describes how SDC measures almost always destroy the ability of researchers to accurately analyze complex survey data. These results are in conflict with increasing trends toward greater transparency in the social sciences. A discussion of the future of SDC concludes the article
Computer security · Data science · Field (mathematics · Information privacy · Internet privacy · Sociology · Transparency (behavior · Computer Science · Data Quality and Management · Ethics in Clinical Research · Privacy-Preserving Technologies in Data
| Citations per year | 0.14 |
|---|---|
| Citation span | 2019 - 2019 (1) |
| Highly cited | No |