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Network Analysis of Readers' Countries of Korean Studies using Mendeley Co-readership Data

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2018, v.35 no.4, pp.107-124
https://doi.org/10.3743/KOSIM.2018.35.4.107


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Abstract

Mendeley readership data could be used to understand how research outcome be spent outside of academia in multi way. So it could be utilized to understand unknown world which citation rate could not explain still now. This study, by conducting a country network analysis using Mendeley’s co readership data about articles of Korea related research, clusters countries that share common academic interest. As a result, the US and other advanced countries in all fields showed high overall and regional centrality, indicating that they have overall cooperation and potential for exchange of Korea related studies. Some developing countries have shown high regional centrality and are linked to common academic interests. In the medical and social sciences, the OECD and developing countries have formed a separate group of readers, and the engineering sector has been characterized by emerging developing countries as a large community of readers. In addition, engineering science field has shown that network density is relatively high, so there might be high possibility of academic exchanges, knowledge dissemination and cooperation among countries.

keywords
Mendeley, co-readership, 네트워크 분석, altmetrics, Mendeley, co-readership, network analysis, altmetrics

Reference

1.

이재윤. (2006). 지적 구조 분석을 위한 새로운 클러스터링 기법에 관한 연구. 정보관리학회지, 23(4), 215-231.

2.

이재윤. (2013). tnet과 WNET의 가중 네트워크 중심성 지수 비교 연구. 정보관리학회지, 30(4), 241-264. http://dx.doi.org/10.3743/KOSIM.2013.30.4.241.

3.

정대현. (2014). 국가 간 공동연구 네트워크 밀도가 기술 확산에 미치는 영향 분석: 이차전지, 전기자동차 분야 사례를 중심으로. 한국콘텐츠학회 논문지, 14(9), 582-588. http://dx.doi.org/10.5392/JKCA.2014.14.09.582.

4.

조재인. (2015). Altmetrics를 통한 연구의 영향력 평가에 관한 연구. 한국도서관·정보학회지, 46(1), 65-81. http://dx.doi.org/10.16981/kliss.46.1.201503.65.

5.

조재인. (2017). Mendeley를 통한 문헌정보학 주요 분야 연구 논문의 독자 분석. 한국도서관·정보학회지, 48(1), 77-97. http://dx.doi.org/10.16981/kliss.48.1.201703.77.

6.

Bornmann, L.. (2015). Alternative metrics in scientometrics: A meta-analysis of research into three altmetrics. Scientometrics, 103(3), 1123-1144.

7.

Cho, Jane.. (2017). A comparative study of the impact of Korean research articles in four academic fields using altmetrics. Performance Measurement and Metrics, 18(1), 38-51.

8.

Hammarfelt, B.. (2014). Using altmetrics for assessing research impact in the humanities. Scientometrics, 101(2), 1419-1430.

9.

Robin Haunschild. (2015). F1000Prime: an analysis of discipline-specific reader data from Mendeley. F1000Research, 4, 41-. http://dx.doi.org/10.12688/f1000research.6062.2.

10.

Robin Haunschild. (2015). Networks of reader and country status: an analysis of Mendeley reader statistics. PeerJ Computer Science, 1, e32-. http://dx.doi.org/10.7717/peerj-cs.32.

11.

Stefanie Haustein. (2015). Characterizing Social Media Metrics of Scholarly Papers: The Effect of Document Properties and Collaboration Patterns. PLOS ONE, 10(3), e0120495-. http://dx.doi.org/10.1371/journal.pone.0120495.

12.

Peter Kraker. (2015). Visualization of co-readership patterns from an online reference management system. Journal of Informetrics, 9(1), 169-182. http://dx.doi.org/10.1016/j.joi.2014.12.003.

13.

Loet Leydesdorff. (2016). Journal portfolio analysis for countries, cities, and organizations: Maps and comparisons. Journal of the Association for Information Science and Technology, 67(3), 741-748. http://dx.doi.org/10.1002/asi.23551.

14.

Li, X.. (2012). F1000, Mendeley and traditional bibliometric indicators (541-551). Proceedings of the 17th International Conference on Science and Technology Indicators.

15.

Ehsan Mohammadi. (2014). Mendeley readership altmetrics for the social sciences and humanities: Research evaluation and knowledge flows. Journal of the Association for Information Science and Technology, 65(8), 1627-1638. http://dx.doi.org/10.1002/asi.23071.

16.

Ehsan Mohammadi. (2014). Mendeley readership altmetrics for the social sciences and humanities: Research evaluation and knowledge flows. Journal of the Association for Information Science and Technology, 65(8), 1627-1638. http://dx.doi.org/10.1002/asi.23071.

17.

Ehsan Mohammadi. (2015). Who reads research articles? An altmetrics analysis of Mendeley user categories. Journal of the Association for Information Science and Technology, 66(9), 1832-1846. http://dx.doi.org/10.1002/asi.23286.

18.

Pardeep Sud. (2016). Not all international collaboration is beneficial: The Mendeley readership and citation impact of biochemical research collaboration. Journal of the Association for Information Science and Technology, 67(8), 1849-1857. http://dx.doi.org/10.1002/asi.23515.

19.

Zohreh Zahedi. (2014). How well developed are altmetrics? A cross-disciplinary analysis of the presence of ‘alternative metrics’ in scientific publications. Scientometrics, 101(2), 1491-1513. http://dx.doi.org/10.1007/s11192-014-1264-0.

Journal of the Korean Society for Information Management