The advent of large language models (LLMs) and their adoption by the legal community has
given rise to the question: what types of legal reasoning can LLMs perform? To enable …

Objectives To investigate whether and what user data are collected by health related mobile
applications (mHealth apps), to characterise the privacy conduct of all the available mHealth …

Transformer-based language models (TLMs) have widely been recognized to be a cutting-
edge technology for the successful development of deep-learning-based solutions to …

Tracking is a highly privacy-invasive data collection practice that has been ubiquitous in
mobile apps for many years due to its role in supporting advertising-based revenue models …

Automated analysis of privacy policies has proved a fruitful research direction, with
developments such as automated policy summarization, question answering systems, and …

Dark patterns are user interface elements that can influence a person's behavior against
their intentions or best interests. Prior work identified these patterns in websites and mobile …

While many studies have looked at privacy properties of the Android and Google Play app
ecosystem, comparatively much less is known about iOS and the Apple App Store, the most …

Standardized privacy labels that succinctly summarize those data practices that people are
most commonly concerned about offer the promise of providing users with more effective …

Website privacy policies sometimes provide users the option to opt-out of certain collections
and uses of their personal data. Unfortunately, many privacy policies bury these instructions …

We analyse Stack Overflow (SO) to understand challenges and confusions developers face
while dealing with privacy-related topics. We apply topic modelling techniques to 1,733 …