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Multi-domain Alias Matching Using Machine Learning
2016
2016 Third European Network Intelligence Conference (ENIC)
We describe a methodology for linking aliases belonging to the same individual based on a user's writing style (stylometric features extracted from the user generated content) and her time patterns (time-based features extracted from the publishing times of the user generated content). While most previous research on social media identity linkage relies on matching usernames, our methodology can also be used for users who actively try to choose dissimilar usernames when creating their aliases.
doi:10.1109/enic.2016.019
dblp:conf/enic/AshcroftJKS16
fatcat:irpr3u544revpkqbbk5imbgw5e