Skip to Main content Skip to Navigation

Matching user accounts across online social networks : methods and applications

Oana Goga 1
1 NPA - Networks and Performance Analysis
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : The proliferation of social networks and all the personal data that people share brings many opportunities for developing exciting new applications. At the same time, however, the availability of vast amounts of personal data raises privacy and security concerns.In this thesis, we develop methods to identify the social networks accounts of a given user. We first study how we can exploit the public profiles users maintain in different social networks to match their accounts. We identify four important properties – Availability, Consistency, non- Impersonability, and Discriminability (ACID) – to evaluate the quality of different profile attributes to match accounts. Exploiting public profiles has a good potential to match accounts because a large number of users have the same names and other personal infor- mation across different social networks. Yet, it remains challenging to achieve practically useful accuracy of matching due to the scale of real social networks. To demonstrate that matching accounts in real social networks is feasible and reliable enough to be used in practice, we focus on designing matching schemes that achieve low error rates even when applied in large-scale networks with hundreds of millions of users. Then, we show that we can still match accounts across social networks even if we only exploit what users post, i.e., their activity on a social networks. This demonstrates that, even if users are privacy conscious and maintain distinct profiles on different social networks, we can still potentially match their accounts. Finally, we show that, by identifying accounts that correspond to the same person inside a social network, we can detect impersonators.
Document type :
Complete list of metadata

Cited literature [179 references]  Display  Hide  Download
Contributor : Abes Star :  Contact Connect in order to contact the contributor
Submitted on : Thursday, June 18, 2015 - 12:05:43 PM
Last modification on : Friday, January 8, 2021 - 5:38:04 PM
Long-term archiving on: : Tuesday, September 15, 2015 - 6:40:40 PM


Version validated by the jury (STAR)


  • HAL Id : tel-01165052, version 1


Oana Goga. Matching user accounts across online social networks : methods and applications. Web. Université Pierre et Marie Curie - Paris VI, 2014. English. ⟨NNT : 2014PA066167⟩. ⟨tel-01165052⟩



Record views


Files downloads