Linky: Visualizing User Identity Linkage Results For Multiple Online Social Networks
Roy Ka-Wei Lee, Ming Shan Hee, Philips Kokoh Prasetyo, Ee-Peng Lim

TL;DR
Linky is a visual analytical tool that helps researchers compare and analyze user identity linkage results across multiple social networks at the individual user level, focusing on profile, content, and network information.
Contribution
The paper introduces Linky, a novel visualization tool for detailed comparison of user identity linkage methods at the individual level across social networks.
Findings
Enables visual comparison of linked user profiles, content, and networks.
Assists in understanding the strengths and weaknesses of different linkage methods.
Supports empirical analysis of factors contributing to linkage accuracy.
Abstract
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…
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Taxonomy
TopicsComplex Network Analysis Techniques · Advanced Graph Neural Networks · Data Quality and Management
