Mit freundlichen Gruessen, With kind regards, Sincères salutations,
H. Peter OHLY ------------------------------------- GESIS - Leibniz-Institut für Sozialwissenschaften / Abt. Fachinformation für die Sozialwissenschaften / Lennestr. 30 / 53113 BONN / Germany / Tel.: +49-228-2281-542 / Fax.: +49-228-2281-4542 / mailto:peter.o...@gesis.org http://www.gesis.org/SocioGuide / http://www.isko.org/people.html Visitors Address: GESIS - Leibniz-Institut für Sozialwissenschaften / Bereich Produkte & Marketing / Dreizehnmorgenweg 42 / 53175 BONN (Metro-Stop: Platz der Vereinten Nationen / Olof-Palme-Allee) -----Original Message----- From: ASIS&T Special Interest Group on Metrics [mailto:sigmetr...@listserv.utk.edu] On Behalf Of Mike Thelwall Sent: Wednesday, November 04, 2009 7:49 PM To: sigmetr...@listserv.utk.edu Subject: [SIGMETRICS] PhD Studentship in Webometric methods to assess emerging research fields Adminstrative info for SIGMETRICS (for example unsubscribe): http://web.utk.edu/~gwhitney/sigmetrics.html PhD Studentship in Webometric methods to assess emerging research fields A significant part of the effort in the research field of scientometrics is devoted to tracking new and emerging scientific fields by analysing their publications in standard databases like the web of science. This approach suffers from an inevitable time lag due to the publication cycle. The objective of this PhD is to develop web-based methods to track heterogeneous emerging research fields, bypassing the publishing time lag and encompassing commercial, governmental and other actors that would not be fully represented in traditional academic publishing. This research will build upon pilot studies already conducted at Wolverhampton. The candidate will ideally have some knowledge of bibliometrics or scientometrics and interview or qualitative analysis techniques. The PhD will combine quantitative and qualitative approaches and would suit someone with a library and information science background. Funding is available for a three-year full-time PhD. Essential: Degree in information science, mathematics or related discipline. Ability to use novel software and do simple analyses of quantitative data. Optional: Master's degree. Experience of writing scientific articles. Experience of interviewing and interview analysis. Knowledge of bibliometrics, scientometrics, webometrics, social network analysis, science studies. Programming experience. For more information see: http://cybermetrics.wlv.ac.uk/phd_2009a.htm
