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Article Title

Method to Determine the Same Users on Multiple Social Networks

Abstract

Each social network used by users for different purposes contains different user data. Finding users' accounts in different social networks and combining the data found and compiling them into a single repository will be a very important factor that will both improve the recommended systems and increase the user experience. Within the scope of the study, original node alignment and node similarity methods are proposed. While using the anchor method in topological-based node proposition, density relationships between the links are also taken into consideration. In the similarity based node similarity method, attribute selection criteria, starting point detection problem and variable formulation have increased the number of successful node matching. However, in this study, alignment and similarity were determined both according to the profile characteristics of the users and the relationships between them. Nine different methods have been proposed to find the same accounts in different social networks. Proposed methods Tested on social networks collected in social network data ranging from two to six, and match success rates of users were measured. In these results, success rates up to 95% have been achieved. Thus, it is possible to create a wide user profile covering multiple social networks for users whose different attributes are gathered on the same graph in multiple social networks.

https://dergipark.org.tr/tr/download/article-file/1181658

DOI

10.24012/dumf.761949

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