Topics in the literature of transition economies and emerging markets

Scientometrics

Volumn 102, Issue 3, 2015, Pages 2107-2130

  Piepenbrink, Anke ^a   Nurmammadov, Elkin ^a  

^a ADA UNIVERSITY   (Azerbaijan)

Author keywords

Economics; Emerging markets; International business; Topic models; Transition economies

Indexed keywords

EID: 84925544975     PISSN: 01389130     EISSN: 15882861     Source Type: Journal    
DOI: 10.1007/s11192-014-1513-2     Document Type: Article

References (38)

1. An, X., & Wu, Q. (2011). Co-word analysis of the trends in stem cells field based on subject heading weighting. Scientometrics, 88(1), 133–144.
2. Azerbaijani Presidential Administration. (2012). Azerbaijan 2020: Look into the future. http://www.presidentaz/files/future-enpdf.
3. Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 7784.
4. Blei, D. M., & Lafferty, J. D. (2006). Dynamic topic models. In Proceedings of the 23rd international conference on machine learning.
5. Blei, D. M., & Lafferty, J. D. (2007a). A correlated topic model of science. The Annals of Applied Statistics, 1(1), 17–35.
6. Blei, D. M., & Lafferty, J. D. (2007b). Topic Models. In A. Srivastava and M. Sahami (Ed.), Text Mining: Classification, Clustering, and Applications. Chapman & Hall/CRC Data Mining and Knowledge Discovery Series.
7. Blei, D. M., Ng, A. Y., Jordan, M. I., & Lafferty, J. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3(4/5), 993–1022.
8. Buckley, P. J. (2002). Is the international business research agenda running out of steam? Journal of International Business Studies, 33(2), 365–373.
9. Callon, M., Courtial, J., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics, 22(1), 155–205.
10. Campos, N., & Coricelli, F. (2002). Growth in transition: What we know, what we don’t know, and what we should. Journal of Economic Literature, 40(3), 793–836.
11. Chandra, R., & Newburry, W. (1997). A cognitive map of the international business field. International Business Review, 6(4), 387–410.
12. Chang, J., Boyd-Graber, J., Wang, C., Gerrish, S., & Blei, D. M. (2009). Reading tea leaves: How humans interpret topic models. In Neural Information Processing Systems.
13. Feinerer, I., Hornik, K., & Meyer, D. (2008). Text mining infrastructure in R. Journal of Statistical Software, 25(5), 1–54.
14. Fischer, S., Sahay, R., & Vegh, C. (1996). Economies in transition: The beginnings of growth. American Economic Review, 86(2), 229–233.
15. Godoy, S., & Stiglitz, J. (2006). Growth, initial conditions, law and speed of privatization in transition countries: 11 years later. NBER Working Paper No 11992.
16. Griffith, D. A., Cavusgil, S. T., & Xu, S. (2008). Emerging themes in international business research. Journal of International Business Studies, 39(7), 1220–1235.
17. Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences of the United States of America, 101, 5228–5235.
18. Grün, B., & Hornik, K. (2011). topicmodels: An R package for fitting topic models. Journal of Statistical Software, 40(13), 1–30.
19. Havrylyshyn, O. (2001). Recovery and growth in transition: A decade of evidence. IMF Staff Papers, 48, 53–87.
20. Hofer, K., Smejkal, A., Bilgin, F., & Wuehrer, G. (2010). Conference proceedings as a matter of bibliometric studies: The academy of international business 2006–2008. Scientometrics, 84(3), 845–862.
21. Kearney, C. (2012). Emerging markets research: Trends, issues and future directions. Emerging Markets Review, 13(2), 159–183.
22. Lamirel, J. C. (2012). A new approach for automatizing the analysis of research topics dynamics: Application to optoelectronics research. Scientometrics, 93(1), 151–166.
23. Lee, B., & Jeong, Y. I. (2008). Mapping Korea’s national R&D domain of robot technology by using the co-word analysis. Scientometrics, 77(1), 3–19.
24. Liesch, P., Hkanson, L., McGaughey, S., Middleton, S., & Cretchley, J. (2011). The evolution of the international business field: a scientometric investigation of articles published in its premier journal. Scientometrics, 88(1), 17–42.
25. Liu, G. Y., Hu, J. M., & Wang, H. L. (2012). A co-word analysis of digital library field in China. Scientometrics, 91(1), 203–217.
26. Melo, M., Denizer, C., & Gelb, A. (1996). Patterns of transition from plan to market. The World Bank Economic Review, 10(3), 397–424.
27. Natale, F., Fiore, G., & Hofherr, J. (2012). Mapping the research on aquaculture. A bibliometric analysis of aquaculture literature. Scientometrics, 90(3), 983–999.
28. Nazarbayev, N. (2012) Strategy Kazakhstan 2050. http://www.akorda.kz/en/page/page_poslanie-prezidenta-respubliki-kazakhstanlidera-natsii-nursultana-nazarbaeva-narodu-kazakhstana.
29. Ponweiser, M. (2012). Latent Dirichlet allocation in R. Master’s thesis, Vienna University of Economics and Business, Institute for Statistics and Mathematics.
30. Popov, V. (2007). Shock therapy versus gradualism reconsidered: Lessons from transition economies after 15 years of reforms. Comparative Economic Studies, 49(1), 1–31.
31. R CoreTeam. (2013). R: A language and environment for statistical computing. Vienna, Austria.
32. Scimago. (2013). http://www.scimagojrcom/journalrankphp.
33. Seitenova, A. G., & Becker, C. (2004). Kazakhstan’s pension system: Pressures for change and dramatic reforms. Hitotsubashi Journal of Economics, 45(2), 151–187.
34. Song, M., & Kim, S. (2012). Detecting the knowledge structure of bioinformatics by mining full-text collections. Scientometrics, 96(1), 183–201.
35. Su, H. N., & Lee, P. C. (2010). Mapping knowledge structure by keyword co-occurrence: A first look at journal papers in technology foresight. Scientometrics, 85(1), 65–79.
36. Wallach, H. M., Murray, I., Salakhutdinov, R., & Mimno, D. (2009). Evaluation methods for topic models. In: Proceedings of the 26th international conference on machine learning.
37. Wuehrer, G., & Smejkal, A. (2013). The knowledge domain of the academy of international business studies (aib) conferences: A longitudinal scientometric perspective for the years 2006–2011. Scientometrics, 95(2),541–561.
38. Yi, S., & Choi, J. (2012). The organization of scientific knowledge: The structural characteristics of keyword networks. Scientometrics, 90(3), 1015–1026.