A Cross-Platform Collection of Social Network Profiles
This provides a resource for researchers to analyze cross-platform privacy risks, but it is incremental as it focuses on data collection rather than new methods.
The paper tackles the problem of studying privacy hazards and user de-anonymization across social media by presenting a dataset of 850 users with profiles on Twitter, Instagram, and Foursquare, containing over 2.5M tweets, 340k check-ins, and 42k Instagram posts.
The proliferation of Internet-enabled devices and services has led to a shifting balance between digital and analogue aspects of our everyday lives. In the face of this development there is a growing demand for the study of privacy hazards, the potential for unique user de-anonymization and information leakage between the various social media profiles many of us maintain. To enable the structured study of such adversarial effects, this paper presents a dedicated dataset of cross-platform social network personas (i.e., the same person has accounts on multiple platforms). The corpus comprises 850 users who generate predominantly English content. Each user object contains the online footprint of the same person in three distinct social networks: Twitter, Instagram and Foursquare. In total, it encompasses over 2.5M tweets, 340k check-ins and 42k Instagram posts. We describe the collection methodology, characteristics of the dataset, and how to obtain it. Finally, we discuss a common use case, cross-platform user identification.