Open AccessUser Identification Based on Display Names Across Online Social Networks
Author(s) -
Yongjun Li,
You Peng,
Wenli Ji,
Zhen Zhang,
Quanqing Xu
Publication year - 2017
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2744646
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
User identification is very helpful for building a better profile of a user. Some works have been devoted to this issue. However, the existing works with a good performance are mainly based on the rich online data and do not consider the cost of online data acquisition. In this paper, we aim to address this issue with a lower cost of data acquisition. A machine learning-based solution is proposed solely based on the user’s display names. It consists of three key steps: we first analyze the users’ unique naming patterns that lead to information redundancies across sites; second, we construct features that exploit information redundancies; afterward, we employ machine learning method for user identification. The experiment shows that the proposed solution can provide excellent performance with F1 score reaching 96.24%, 92.49%, and 90.68% on three real different data sets, respectively. This paper shows the possibility of user identification with a lower cost of data acquisition.
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