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Sampling labelled profile data for identity resolution

Research output: Contribution in Book/Report/ProceedingsConference contribution

Published
Publication date5/12/2016
Host publicationProceedings of IEEE International Conference on Big Data (IEEE BigData 2016)
PublisherIEEE
Pages540-547
Number of pages8
ISBN (Electronic)9781467390057
ISBN (Print)9781467390064
<mark>Original language</mark>English
Event2016 IEEE International Conference on Big Data (Big Data) - Washington, D.C., United States

Conference

Conference2016 IEEE International Conference on Big Data (Big Data)
CountryUnited States
CityWashington, D.C.
Period5/12/168/12/16
Internet address

Conference

Conference2016 IEEE International Conference on Big Data (Big Data)
CountryUnited States
CityWashington, D.C.
Period5/12/168/12/16
Internet address

Abstract

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.

Bibliographic note

©2016 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.