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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (3): 30-38    DOI: 10.11925/infotech.2096-3467.2017.0822
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Identifying Interdisciplinary Social Science Research Based on Article Classification
Liu Liu1,2(),Dongbo Wang2,3
1(School of Information Management, Nanjing University, Nanjing 210023, China)
2(Jiangsu Key Laboratory of Data Engineering and Knowledge Service (Nanjing University), Nanjing 210023, China)
3(College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095, China)
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[Objective] This study aims to quantitatively examine the interdisciplinary social science research with the help of machine learning technique’s automatic classification method. [Methods] We used the KNN algorithm to classify social science papers indexed by CNKI and then proposed a new method to calculate their degree of interdisciplinarity. [Results] There was significant difference among classification results of all disciplines. We also found significant correlation between the classification results and interdisciplinarity of papers. [Limitations] More quantitative research is needed to expand the present study. [Conclusions] Machine learning could effectively identify the interdisciplinary social science studies.

Key wordsKNN      Text Classification      Interdisciplinarity     
Received: 15 August 2017      Published: 03 April 2018

Cite this article:

Liu Liu,Dongbo Wang. Identifying Interdisciplinary Social Science Research Based on Article Classification. Data Analysis and Knowledge Discovery, 2018, 2(3): 30-38.

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