Privacy dictionary: a linguistic taxonomy of privacy for content analysis

Privacy is frequently a key concern relating to technology and central to HCI research, yet it is notoriously difficult to study in a naturalistic way. In this paper we describe and evaluate a dictionary of privacy designed for content analysis, derived using prototype theory and informed by traditional theoretical approaches to privacy. We evaluate our dictionary categories alongside privacy-related categories from an existing content analysis tool, LIWC, using verbal discussions of privacy issues from a variety of technology and non-technology contexts. We find that our privacy dictionary is better able to distinguish between privacy and non-privacy language, and is less context-dependent than LIWC. However, the more general LIWC categories are able to describe a greater amount of variation in our data. We discuss possible improvements to the privacy dictionary and note future work.