  User identity linkage across online social networks is an emerging research
topic that has attracted attention in recent years. Many user identity linkage
methods have been proposed so far and most of them utilize user profile,
content and network information to determine if two social media accounts
belong to the same person. In most cases, user identity linkage methods are
evaluated by performing some prediction tasks with the results presented using
some overall accuracy measures. However, the methods are rarely compared at the
individual user level where a predicted matched (or linked) pair of user
identities from different online social networks can be visually compared in
terms of user profile (e.g. username), content and network information. Such a
comparison is critical to determine the relative strengths and weaknesses of
each method. In this work, we present Linky, a visual analytical tool which
extracts the results from different user identity linkage methods performed on
multiple online social networks and visualizes the user profiles, content and
ego networks of the linked user identities. Linky is designed to help
researchers to (a) inspect the linked user identities at the individual user
level, (b) compare results returned by different user linkage methods, and (c)
provide a preliminary empirical understanding on which aspects of the user
identities, e.g. profile, content or network, contributed to the user identity
linkage results.
