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Articles

User identification across multiple online social networks using cross link attribute and network relationship

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Abstract

An online user creates accounts on numerous social platforms to fulfill his/her needs. The user shares interactive content through posts/tweets and communicates with friends and colleagues. In this paper, we inspect the problem of social accounts matching across social media services by proposing a two-step method. In the first step, the proposed method uses cross-link posts to get the seed users’ accounts. After that, it utilizes the network features of the seed user and finds the association between the network relationships (follower and following) of the same user. By evaluating the experimental results, we found that the accuracy achieved by the proposed technique with the exact username is 98% and while the accuracy reduces to 45% when username across the sites is differed by one character.

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