Algorithm for Applying Statistics and Scientometric Analysis to Identify Innovative Areas of Focus in Scientific Knowledge in Labour Economics
https://doi.org/10.34023/2313-6383-2019-26-2-53-66
Abstract
The modern Digital Universe changes and expands at a speed that every two years double the amount of data. It leads to a situation when huge accumulated flows of information can no longer be covered by traditional scientific search and built into a relevant scientific research framework. The authors argue that there is a need for using modern statistics and scientometric application packages for solving research tasks in the primary trends of the information economy. The article presents a comparative analysis of various scientometric programs and describes a new approach to identifying and visualizing patterns and transient regularities in the scientific literature on the basis of a study of global publication flows in the last 25 years in the subject area of «labour economics» represented in the Web of Science.
The authors conceptualize and visualize scientific domain of «labour economics» within the framework of the timing diagram of the evolution of research fronts. They introduce the search algorithm for active research fronts in the global information flow using CiteSpace V.0 and highlight the most critical trends and principal points of research clusters for the past decade on labour economics and its core studies. The paper determines most perspective citation spikes that could potentially become the center of new scientific knowledge in this area and outlines opportunities for future research.
Supporting agencies: Russian Foundation for Basic Research
About the Authors
O. E. Bashina
Moscow University for the Humanities
Russian Federation
Russian Federation
Olga E. Bashina - Dr. Sci. (Econ.), Professor, Head, Department of Statistics, Marketing and Accounting
5, Yunosti St., Moscow, 111395
L. V. Matraeva
Russian State Social University
Russian Federation
Russian Federation
Liliia V. Matraeva - Dr. Sci. (Econ.), Docent, Professor, Department of Economic Theory and World Economy
4, Wilhelm Pieck St., build.5, Moscow, 129226
Ye. S. Vasyutina
Russian State Social University
Russian Federation
Russian Federation
Yekaterina S. Vasyutina- Cand. Sci. (Econ.), Docent, Department of Economic Theory and World Economy
4, Wilhelm Pieck St., build.5, Moscow, 129226
References
1. Fursov K.S. Russia in Global Science: the Results of Bibliometric Analysis. In: Naukovedcheskie Issledovaniya. Yearbook: Collection of Research Papers. Moscow: INION RAS; 2015. P.61-79. (In Russ.)
2. Izmalkova S.A., Golovina T.A. Use of the Global Technologies «Big Data» in Management of Economic Systems. Tula State University. Economic and Legal Sciences. 2015;4(1):151-158. (In Russ.)
3. Matraeva L.V., Bashina O.E. Modern Trends in the Use of Technology Big data in Economic Processes in the Practice of Foreign and Domestic Companies. Economics and Entrepreneurship. 2017; 5-1(82-1):788-791. (In Russ.)
4. Persson O. The Intellectual Base and Research Fronts of JASIS 1986-1990. Journal of the American Society for Information Science. 1994;45(1):31-38.
5. Kessler M.M. Bibliographic Coupling Between Scientific Papers. American Documentation. 1963;(14):10-25.
6. Yeremchenko O.A., Aliev V.O. Comparative analysis of research strategies and social sciences in Russia and in the world. The Economics of Science. 2015;1(1):48-61. (In Russ.)
7. Upham S.P., Small H. Emerging Research Fronts in Science and Technology: Patterns of New Knowledge Development. Scientometrics. 2010;83(1):15-38.
8. Mazov NA, Gureev V.N. Programs for Scientometric and Bibliometric Research: a Brief Review and a Comparative Analysis. In: Proceedings of the 15th All-Russian Scientific Conference «Digital Libraries: Advanced Methods and Technologies, Digital Collections» - RCDL-2013, Yaroslavl, Russia, 14-17 October 2013. (In Russ.)
9. Mazov N.A. Free Software for Scientometric and Bibliometric Research. In: Libraries and Information Resources in the Modern World of Science, Culture, Education and Business: 19 th International. Conf. «Crimea 2012». Moscow: Publishing House of the Russian National Public Library for Science and Technology; 2012. P.1-6. (In Russ.)
10. Chen Ch. CiteSpace II: Detecting and Visualizing Emerging Trends and Transient Patterns in Scientific Literature. Journal o� the American Society for Information Science and Technology. 2006;57(3):359-377.
11. Analytical Report on the Results of the First Phase of Research on the Topic. Update of the Long-Term Forecast of the Most Important Areas of Scientific and Technological Development for the Period Until 2030. National Research University Higher School of Economics. (In Russ.) Available from: https://www.hse.ru/data/2012/03/05/1266648817/Doc_HEHE_expandation%20prognosis.pdf. (accessed 13.03.18)
12. Small H. Paradigms, citations, and maps of science: A personal history. Journal of the American Society for Information Science and Technology. 2003;54(5):394-399.
13. Acemoglu D., David D. Import Competition and the Great US Employment Sag of the 2000s . Journal O� Labor Economics.2016;34(l):141-S198.
14. Autor D., Dorn D., Hanson G.H. The China Shock: Learning from Labor-Market Adjustment to Large Changes in Trade. Annual Review of Economics. 2016;(8):205-240.
15. Staehler N., Thomas C. FiMod A DSGE Model for Fiscal Policy Simulations. Economic Modelling. 2011;29(20):239-261.
16. Helpman E., Itskhoki O. Labour Market Rigidities, Trade and Unemployment. Review of Economic Studies. 2010;77(3):1100-1137.
17. Demurger S., Xu H. Return Migrants: The Rise of New Entrepreneurs in Rural China. World Development. 2011;39(10):1847-1861.
18. Wang X., Huang J., Zhang L., Rozelle S. The rise of migration and the fall of Self-Employment in Rural China’s Labor Market. China Economic Review. 2011;22(4):573-584.
19. Piketty T. Capital in Twenty-First Century. Harvard University Press. 2014. P. 686.
Review
For citations:
Bashina O.E., Matraeva L.V., Vasyutina Ye.S. Algorithm for Applying Statistics and Scientometric Analysis to Identify Innovative Areas of Focus in Scientific Knowledge in Labour Economics. Voprosy statistiki. 2019;26(2):53-66. (In Russ.) https://doi.org/10.34023/2313-6383-2019-26-2-53-66
Views:
768
Email this article 