Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
11-2018
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 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.
Keywords
social network, user identity linkage, visualization
Discipline
Databases and Information Systems | Social Media
Research Areas
Data Science and Engineering
Publication
2018 IEEE International Conference on Data Mining Workshops 18th ICDMW: Singapore, November 17-20: Proceedings
First Page
1453
Last Page
1458
ISBN
9781538692882
Identifier
10.1109/ICDMW.2018.00207
Publisher
IEEE Computer Society
City or Country
Los Alamitos, CA
Citation
LEE, Roy Ka-Wei; HEE, Ming Shan; PRASETYO, Philips Kokoh; and LIM, Ee-Peng.
Linky: Visualizing user identity linkage results for multiple online social networks (Demo). (2018). 2018 IEEE International Conference on Data Mining Workshops 18th ICDMW: Singapore, November 17-20: Proceedings. 1453-1458.
Available at: https://ink.library.smu.edu.sg/sis_research/4262
Copyright Owner and License
Authors/LARC
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/ICDMW.2018.00207