{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T00:27:42Z","timestamp":1777854462170,"version":"3.51.4"},"reference-count":22,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2016,10,1]],"date-time":"2016-10-01T00:00:00Z","timestamp":1475280000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Information Science"],"published-print":{"date-parts":[[2018,6]]},"abstract":"<jats:p>To take advantage of the full range of services that online social networks (OSNs) offer, people commonly open several accounts on diverse OSNs where they leave lots of different types of profile information. The integration of these pieces of information from various sources can be achieved by identifying individuals across social networks. In this article, we address the problem of user identification by treating it as a classification task. Relying on common public attributes available through the official application programming interface (API) of social networks, we propose different methods for building negative instances that go beyond usual random selection so as to investigate the effectiveness of each method in training the classifier. Two test sets with different levels of discrimination are set up to evaluate the robustness of our different classifiers. The effectiveness of the approach is measured in real conditions by matching profiles gathered from Google+, Facebook and Twitter.<\/jats:p>","DOI":"10.1177\/0165551516673480","type":"journal-article","created":{"date-parts":[[2016,10,22]],"date-time":"2016-10-22T00:13:23Z","timestamp":1477095203000},"page":"377-391","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["User identification across online social networks in practice: Pitfalls and solutions"],"prefix":"10.1177","volume":"44","author":[{"given":"Azadeh","family":"Esfandyari","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matteo","family":"Zignani","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sabrina","family":"Gaito","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gian Paolo","family":"Rossi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2016,10,1]]},"reference":[{"key":"bibr1-0165551516673480","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2008.08.022"},{"key":"bibr2-0165551516673480","first-page":"360","volume-title":"Proceedings of the first international conference on networked digital technologies (NDT \u201909)","author":"Vosecky J"},{"key":"bibr3-0165551516673480","doi-asserted-by":"publisher","DOI":"10.1016\/j.datak.2009.10.003"},{"key":"bibr4-0165551516673480","unstructured":"Winkler WE. The state of record linkage and current research problems. 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In: Proceedings of the 22nd international conference on world wide web (WWW \u201913 companion), Rio de Janeiro, Brazil, 13\u201317 May 2013, pp. 1259\u20131268. 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