Sampling labelled profile data for identity resolution

Edwards, Matthew and Wattam, Stephen Michael and Rayson, Paul Edward and Rashid, Awais (2016) Sampling labelled profile data for identity resolution. In: Proceedings of IEEE International Conference on Big Data (IEEE BigData 2016) :. IEEE, USA, pp. 540-547. ISBN 9781467390064

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Identity resolution capability for social networking profiles is important for a range of purposes, from open-source intelligence applications to forming semantic web connections. Yet replication of research in this area is hampered by the lack of access to ground-truth data linking the identities of profiles from different networks. Almost all data sources previously used by researchers are no longer available, and historic datasets are both of decreasing relevance to the modern social networking landscape and ethically troublesome regarding the preservation and publication of personal data. We present and evaluate a method which provides researchers in identity resolution with easy access to a realistically-challenging labelled dataset of online profiles, drawing on four of the currently largest and most influential online social networks. We validate the comparability of samples drawn through this method and discuss the implications of this mechanism for researchers as well as potential alternatives and extensions.

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11 Nov 2016 13:10
Last Modified:
18 May 2024 02:17