Инд. авторы:	Guskov A.E., Bykhovtsev E.S., Kosyakov D.V.
Заглавие:	Alternative webometrics: Study of the traffic of the websites of scientific organizations
Библ. ссылка:	Guskov A.E., Bykhovtsev E.S., Kosyakov D.V. Alternative webometrics: Study of the traffic of the websites of scientific organizations // Scientific and Technical Information Processing. - 2015. - Vol.42. - Iss. 4. - P.274-289. - ISSN 0147-6882. - EISSN 1934-8118.
Внешние системы:	DOI: 10.3103/S0147688215040139; РИНЦ: 26535551; SCOPUS: 2-s2.0-84957051954; WoS: 000420819600009;
Реферат:	eng: The currently existing webometric rankings and methods of their analysis are focused primarily on the quantitative measurement of the contents of websites and almost completely ignore the study of the user audience (web traffic). In a pilot project the traffic of ten websites of scientific organizations has been studied with the emphasis on web-traffic sources and the analysis of the traffic of pages with scientific content. It is shown that the direct visits to the site are an indicator of the regular audience of an organization website. This audience consists mainly of the organization’s staff and their immediate colleagues, while new visitors come mainly from search engines. It was revealed that the most visited pages are the ones with information about staff and laboratories, as well as news pages if they are regularly updated. It was found that there is no strong relationship between webometric rankings and website traffic. The rank correlation is moderate and traffic from external links on other websites is weak despite the fact that such links are a key webometric indicator. The results of the study can be used to optimize the structures of the websites of scientific organizations and the analysis of their user audience. © 2015, Allerton Press, Inc.
Ключевые слова:	webometrics; web traffic; institute websites; Siberian Branch; Russian Academy of Sciences;
Издано:	2015
Физ. характеристика:	с.274-289
Цитирование:	1. Almind, T.C. and Ingwersen, P., Informetric analyses on the World Wide Web: Methodological approaches to “webometrics,” J. Doc., 1997, vol. 53, no. 4, pp. 404-426. 2. Ablameiko, S.V., Zhuravkov, M.A., and Samokhval, V.V., Universities of CIS countries in the world webometric ranking: Analysis based on the profile of their activities, Vyssh. Obraz. Ross., 2013, nos. 8-9, pp. 25-31. 3. Pechnikov, A.A. and Ilyukevich, O.G., Rating of the official web-sites of universities of Russia and Finland: Comparative analysis, Inf. Resursy Ross., 2008, no. 3, pp. 25-28. 4. Ablameiko, S.V., Zhuravkov, M.A., Samokhval, V.V., and Khukhlyndina, L.M., New rankings of universities of countries-participants of the CIS: Correlation with results of the webometric rating, Vyssh. Obraz. Ross., 2014, no. 7, pp. 11-22. 5. Tret'yakova, T.O. and Kabakova, E.A., The possibility of using webometric analysis in the evaluation of the site of a research institute, Vopr. Territ. Razvitiya, 2014, vol. 2, no. 12, pp. 1-10. 6. Antopol'skii, A.B., Polyak, Yu.E., and Usanov, V.E., On the Russian index of web sites of scientific and edu- cational institutions, Inf. Resur. Ross., 2012, no. 4, pp. 2-7. 7. Pechnikov, A.A., Lugovaya, N.B., Chuiko, Yu.V., and Kosinets, I.E., Development of tools for webometric studies of hyperlinks of scientific research sites, Vychisl. Tekhnol., 2009, vol. 14, no. 5, pp. 66-78. 8. Antopol'skii, A.B., Problems of measuring the publica- tion activity of Russian universities on the Internet, Nauchn. Period., Probl. Resheniya, 2013, vol. 3, no. 15, pp. 13-21. 9. Shokin, Yu.I., Klimenko, O.A., and Petrov, I.S., Anal- ysis of the links between the websites of the institutes of the Siberian Branch of RAS, Vestn. Novosib. Gos. Univ., Ser. Inf. Tekhnol., 2011, vol. 9, no. 4, pp. 1-6. 10. Antopolskii, A.B., On the feasibility of the Russian national webometric index, Sci. Tech. Inf. Process., 2014, vol. 41, no. 1, pp. 33-37. 11. Pechnikov, A.A., On measurements of webometric indicators, Mezhdunar. Zh. Eksp. Obraz., 2013, no. 10, pp. 400-404. 12. Mazalov, V.V. and Pechnikov, A.A., On the ranking of scientific institutions of northwest Russia, Upr. Bol'shimi Sist., 2008, no. 24, pp. 130-146. 13. Pechnikov, A.A., Reflections on the webometric rating, Nauchn. Period., Probl. Resheniya, 2014, no. 1, pp. 17-21. 14. Antopol'skii, A.B., The use of information resources for the evaluation of the effectiveness of scientific research, Mezhotrasl. Inf. Sluzhba, 2011, no. 1, pp. 40-53. 15. Aguillo, I.F., Is Google Scholar useful for bibliomet- rics? A webometric analysis, Scientometrics, 2012, vol. 91, no. 2, pp. 343-351. 16. Shokin, Yu.I., Klimenko, O.A., Rychkova, E.V., and Shabal'nikov, I.V., The rating of sites of scientific orga- nizations of the SB RAS, Vychisl. Tekhnol., 2008, vol. 13, no. 3, pp. 128-135. 17. Shokin, Yu.I., Vesnin, A.Yu., Dobrynin, A.A., Kli- menko, O.A., Rychkova, E.V., and Petrov, I.A., A study of the scientific web space of the Siberian Branch of the Russian Academy of Sciences, Vychisl. Tekhnol., 2012, vol. 17, no. 6, pp. 85-98. 18. Pechnikov, A.A., Comparative analysis of the connect- edness of web graphs of scientific institutions, Sovrem. Probl. Nauki Obraz., 2014, no. 3, p. 77. 19. Ortega, J.L. and Aguillo, I.F., Institutional and country collaboration in an online service of scientific profiles: Google Scholar citations, J. Informetrics, 2013, vol. 7, no. 2, pp. 394-403. http://linkinghub.elsevier.com/retrieve/pii/S1751157713000023. Cited August 13, 2014. 20. Aguillo, I.F., Ortega, J.L., and Granadino, B., Con- tents of the Google database: Distribution by country, domain and language, Profesional de la Informacion, 2006, vol. 15, no. 5, pp. 384-389. 21. Más-Bleda, A. and Aguillo, I.F., Can a personal website be useful as an information source to assess individual scientists? The case of European highly cited research- ers, Scientometrics, 2013, vol. 96, no. 1, pp. 51-67. 22. Ortega, J.L., Relationship between altmetric and bib- liometric indicators across academic social sites: The case of CSIC's members, J. Inf., 2015, vol. 9, no. 1, pp. 1-17. http://www.researchgate.net/publication/268444343_Relationship_between_altmetric_and_bib liometric_indicators_across_academic_social_sites_ The_case_of_CSIC's_members 23. Mohammadi, E., Thelwall, M., Haustein, S., and Lariviere, V., Who reads research articles? An altmet- rics analysis of Mendeley user categories, J. Assoc. Inf. Sci. Technol., 2014, vol. 66, no. 9, pp. 1-28. 24. Red'kina, N.S., Formal methods of analysis of docu- mentary information flows, Bibliosfera, 2005, no. 2, pp. 51-59. 25. Moskovkin, V.M., Databases of scientific information and online search tools: The use for knowledge man- agement, Nauchn. Tekh. Bibl., 2012, no. 6, pp. 18-29. 26. Galyavieva, M.S., Altmetrics or new indicators of sci- entific communication in the environment of web 2.0, Uch. Zap. ISGZ, 2014, nos. 1-2 (12), pp. 241-247. 27. Vaughan, L. and Yang, R., Web traffic and organization performance measures: Relationships and data sources examined, J. Informetrics, 2013, vol. 7, no. 3, pp. 699-711. http://linkinghub.elsevier.com/retrieve/pii/S1751157713000412. Cited August 13, 2014. 28. Yang, L. and Perrin, J.M., Library Website Google Ana- lytics Report: An External Review from Digital Resources (Technical Report), Texas Tech University, 2013.http://www.tandfonline.com/doi/full/10.1080/19322909. 2014.944296 29. Andrykovich, K., Wisniewski, E., and Swift, M.S. (Star), How a Google Grant and Google Analytics improved a website: A case example of a university's arbitration and mediation website used by students, business and the public, Int. J. Bus. Adm., 2014, vol. 5, no. 4, pp. 60-69. http://www.sciedu.ca/journal/index. php/ijba/article/view/5119 30. Jorg, B., CERIF: Common European research infor- mation format -insight into the CERIF 2008 -1.1 release, Proc. Int. Conf. on Current Research Information Systems, 2008, pp. 183-192. 31. Guskov, A., Zhizhimov, O., Kikhtenko, V., Skachkov, D., and Kosyakov, D., RuCRIS: A pilot CERIF based sys- tem to aggregate heterogeneous data of Russian research projects, Procedia Comput. Sci., 2014, vol. 33, pp. 163-167. 32. Parinov, S., Towards an open data on how the research data are used: CRIS-CERIF based approach, Procedia Comput. Sci., 2014, vol. 33, pp. 55-59. 33. Eysenbach, G., Citation advantage of open access arti- cles, PLoS Biol., 2006, vol. 4, no. 5, p. e157. http://jour- nals.plos.org/plosbiology/article?id=10.1371/journal. pbio.0040157#pbio-0040157-t004. Cited December 16, 2014. 34. Craig, I., Plume, A., Mcveigh, M., Pringle, J., and Amin, M., Do open access articles have greater citation impact? A critical review of the literature, J. Informet- rics, 2007, vol. 1, no. 3, pp. 239-248.