Linking Multiple Identities in Online Social Networks Based on Co-Occurrence Analysis

Abstract

When tackling the problem of mining multiple fake identities which are controlled by the same individual in internet, traditional techniques used to analyze the posted comments using text-based methods. However, these texts are always in colloquial style which make the effect may not be as obvious as expected. In this paper a new multiple identities linking algorithm is proposed based on the fine-grained analysis of co-occurrence degree of user accounts using sliding window model. Finally, a series of experiments show the effectiveness of our proposed method.