Search (6 results, page 1 of 1)

  • × author_ss:"Oppenheim, C."
  • × type_ss:"a"
  • × year_i:[2000 TO 2010}
  1. Oppenheim, C.: Electronic scholarly publishing and open access (2009) 0.02 
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    Date
    8. 7.2010 19:22:45
    Source
    Information science in transition, Ed.: A. Gilchrist
  2. Oppenheim, C.: Using the h-Index to rank influential British researchers in information science and librarianship (2007) 0.01 
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    Abstract
    The recently developed h-index has been applied to the literature produced by senior British-based academics in librarianship and information science. The majority of those evaluated currently hold senior positions in UK information science and librarianship departments; however, a small number of staff in other departments and retired "founding fathers" were analyzed as well. The analysis was carried out using the Web of Science (Thomson Scientific, Philadelphia, PA) for the years from 1992 to October 2005, and included both secondauthored papers and self-citations. The top-ranking British information scientist, Peter Willett, has an h-index of 31. However, it was found that Eugene Garfield, the founder of modern citation studies, has an even higher h-index of 36. These results support other studies suggesting that the h-index is a useful tool in the armory of bibliometrics.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.2, S.297-301
  3. Ahmed, S.M.Z.; McKnight, C.; Oppenheim, C.: ¬A study of users' performance and satisfaction with the Web of Science IR interface : making sense of it all (2005) 0.01 
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    Source
    Journal of information science. 30(2005) no.5, S.459-
  4. Johnson, B.; Oppenheim, C.: How socially connected are citers to those that they cite? (2007) 0.00 
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    Abstract
    Purpose - The purpose of this paper is to report an investigation into the social and citation networks of three information scientists: David Nicholas, Peter Williams and Paul Huntington. Design/methodology/approach - Similarities between citation patterns and social closeness were identified and discussed. A total of 16 individuals in the citation network were identified and investigated using citation analysis, and a matrix formed of citations made between those in the network. Social connections between the 16 in the citation network were then investigated by means of a questionnaire, the results of which were merged into a separate matrix. These matrices were converted into visual social networks, using multidimensional scaling. A new deviance measure was devised for drawing comparisons between social and citation closeness in individual cases. Findings - Nicholas, Williams and Huntington were found to have cited 527 authors in the period 2000-2003, the 16 most cited becoming the subjects of further citation and social investigation. This comparison, along with the examination of visual representations indicates a positive correlation between social closeness and citation counts. Possible explanations for this correlation are discussed, and implications considered. Despite this correlation, the information scientists were found to cite widely outside their immediate social connections. Originality/value - Social network analysis has not been often used in combination with citation analysis to explore inter-relationships in research teams.
  5. Norris, M.; Oppenheim, C.; Rowland, F.: ¬The citation advantage of open-access articles (2008) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.12, S.1963-1972
  6. Zuccala, A.; Thelwall, M.; Oppenheim, C.; Dhiensa, R.: Web intelligence analyses of digital libraries : a case study of the National electronic Library for Health (NeLH) (2007) 0.00 
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    Abstract
    Purpose - The purpose of this paper is to explore the use of LexiURL as a Web intelligence tool for collecting and analysing links to digital libraries, focusing specifically on the National electronic Library for Health (NeLH). Design/methodology/approach - The Web intelligence techniques in this study are a combination of link analysis (web structure mining), web server log file analysis (web usage mining), and text analysis (web content mining), utilizing the power of commercial search engines and drawing upon the information science fields of bibliometrics and webometrics. LexiURL is a computer program designed to calculate summary statistics for lists of links or URLs. Its output is a series of standard reports, for example listing and counting all of the different domain names in the data. Findings - Link data, when analysed together with user transaction log files (i.e. Web referring domains) can provide insights into who is using a digital library and when, and who could be using the digital library if they are "surfing" a particular part of the Web; in this case any site that is linked to or colinked with the NeLH. This study found that the NeLH was embedded in a multifaceted Web context, including many governmental, educational, commercial and organisational sites, with the most interesting being sites from the.edu domain, representing American Universities. Not many links directed to the NeLH were followed on September 25, 2005 (the date of the log file analysis and link extraction analysis), which means that users who access the digital library have been arriving at the site via only a few select links, bookmarks and search engine searches, or non-electronic sources. Originality/value - A number of studies concerning digital library users have been carried out using log file analysis as a research tool. Log files focus on real-time user transactions; while LexiURL can be used to extract links and colinks associated with a digital library's growing Web network. This Web network is not recognized often enough, and can be a useful indication of where potential users are surfing, even if they have not yet specifically visited the NeLH site.

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