User profiling has existed in the social media since their inception and has supported most of their business model. Even if users do not actively share the information about themselves on the social media (so-called passive users), they can still be profiled based on their location and who they follow. Here we present a system that leverages the linking of followed (popular) Twitter users to DBpedia, and the information therein contained, to help users concealing their digital footprint. Specifically, our approach helps a passive Twitter user to stay private by proposing a list of additional profiles to follow that would confuse the social media’s inference pipeline and prevent it from inferring useful information about that passive user and his interests.
The code in this repository covers the extraction of ISWC authors, mapping the user to category distributon, a number of concealing approaches explained in our paper and the evaluation pipelines to validate our system.
Here you can find a category distribution for each Wikipedia page that we have used in our paper to produce user interests.
The latest version of our paper can be found here
Here we list changes to our paper done since it's publication on CEUR-WS
- Incorrect citation. On page 2, "initially introduced by Piao and Breslin [20]" now reads "initially introduced by Besel et al. [3]"