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Classification analysis of the underprivileged class according to digital divide using machine learning
Journal of the Korean Data & Information Science Society 2021;32:1071-83
Published online September 30, 2021;
© 2021 Korean Data and Information Science Society.

Kwang Yoon Song1 · Youn Su Kim2 · In Hong Chang3

13Department of Computer Science and Statistics, Chosun University
2Department of Computer Science and Statistics, Graduate School, Chosun University
Correspondence to: 1 Research professor, Department of Computer Science and Statistics, ChosunUniversity, Gwangju 61452, Korea.
2 Ph.D. candidate, Department of Computer Science and Statistics, Graduate School, Chosun University, Gwangju 61452, Korea.
3 Corresponding author: Professor, Department of Computer Science and Statistics, Chosun University, Gwangju 61452, Korea. E-mail:
This study was supported by research fund from Chosun University, 2021.
Received August 26, 2021; Revised September 8, 2021; Accepted September 10, 2021.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
The digital divide refers to access to information and refers to a phenomenon that appears disproportionately by economic class, gender, and age. As society develops, the methods of acquiring information are becoming more diverse and easier. The underprivileged class who cannot adapt to these changes are experiencing difficulties different from the digital divide they experienced in the previous PC and wired Internet environments. At present, due to the development of society and various routes through which information can be accessed, another Underprivileged Class is being formed, which has various difficulties in using information and communication devices due to economic, social and physical conditions. In this study, a method was proposed to reduce the gap between the common class, the underprivileged class, and between the underprivileged class using various classification analysis. As a result, it is expected to build an environment that can reduce the information gap by minimizing the cases in which people belonging to the underprivileged class are misclassified as the general class and do not receive appropriate services or benefits. In addition, it is expected that the digital divide with citizens in the general class can be reduced through policy, education, services that are appropriate for the class correctly classified in the underprivileged class.
Keywords : Classification analysis, digital divide, machine learning, support vector machine, underprivileged class.