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Social Network Analysis and Mining

Second-level degree-based entity resolution in online social networks

  • 01-12-2018
  • Original Article
Published in:
Authors
JooYoung Lee
Rasheed Hussain
Victor Rivera
Davlatbek Isroilov
Published in
Social Network Analysis and Mining | Issue 1/2018

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Abstract

Abundance of online social platforms allows users to create more than one profile in different social networks. Several issues arise due to multiple user identities including data integration and information retrieval in social networks. Identifying user profiles across social platforms is known as entity resolution. In this paper, we propose a degree-based method to attack entity resolution problems. More precisely, we utilize the degree of users and their friends to identify user profiles. Our results show that, without help of critical information such as e-mail addresses, the proposed method can outperform existing string matching-based solutions as well as popular classifiers such as SVM and Naive Bayes.

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previous article BullyBlocker: toward an interdisciplinary approach to identify cyberbullying
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Title
Second-level degree-based entity resolution in online social networks
Authors
JooYoung Lee
Rasheed Hussain
Victor Rivera
Davlatbek Isroilov
Publication date
01-12-2018
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2018
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-018-0499-9
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