Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

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. Copyright 2011 ACM.

Original publication




Conference paper

Publication Date



3227 - 3236