Project Description



There is great interest from many companies in matching user profiles across diverse social networks.

Users use different social networks in different ways and it can be a challenging task to match the user activity across these networks, especially if profile information is missing or obfuscated in some way

There is also strong interest in finding users with similar traits (connections, content, names, activity) within the same social network and the SocialIdentityFingerprint system allows the user to apply the cross-network metrics also within a network.


We have developed a web-based search tool which allows the end-user to match users across diverse social networks.


The pre-processing system takes the content in both networks and computes a number of similarity metrics, including:

  • Network similarity (shared connections)
  • Textual similarity (shared words or phrases)
  • Semantic similarity (semantically-related words or phrases across networks) e.g (software, computing, technology)
  • String matching for profile entries (name, email, location)
  • Activity matching (time of day, day of week histograms)



The Social Identity Fingerprint system is particularly useful to companies who wish to aggregate information about users across social media platforms. The system can be applied to any set of data which has a network structure, e.g corporate employee networks, call graphs.


  • Dr Gerard Lynch, UCD
  • Dr Oisín Boydell, UCD
  • Hodei Irola, UCD
  • Dr Brian Mac Namee, UCD