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Hjerppe, R.: ¬An outline of bibliometrics and citation analysis (1980)
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- Type
- r
-
Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003)
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- Abstract
- Ahlgren, Jarneving, and. Rousseau review accepted procedures for author co-citation analysis first pointing out that since in the raw data matrix the row and column values are identical i,e, the co-citation count of two authors, there is no clear choice for diagonal values. They suggest the number of times an author has been co-cited with himself excluding self citation rather than the common treatment as zeros or as missing values. When the matrix is converted to a similarity matrix the normal procedure is to create a matrix of Pearson's r coefficients between data vectors. Ranking by r and by co-citation frequency and by intuition can easily yield three different orders. It would seem necessary that the adding of zeros to the matrix will not affect the value or the relative order of similarity measures but it is shown that this is not the case with Pearson's r. Using 913 bibliographic descriptions form the Web of Science of articles form JASIS and Scientometrics, authors names were extracted, edited and 12 information retrieval authors and 12 bibliometric authors each from the top 100 most cited were selected. Co-citation and r value (diagonal elements treated as missing) matrices were constructed, and then reconstructed in expanded form. Adding zeros can both change the r value and the ordering of the authors based upon that value. A chi-squared distance measure would not violate these requirements, nor would the cosine coefficient. It is also argued that co-citation data is ordinal data since there is no assurance of an absolute zero number of co-citations, and thus Pearson is not appropriate. The number of ties in co-citation data make the use of the Spearman rank order coefficient problematic.
- Date
- 9. 7.2006 10:22:35
-
Page, L.; Brin, S.; Motwani, R.; Winograd, T.: ¬The PageRank citation ranking : Bringing order to the Web (1999)
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Rajan, T.N.; Guha, B.; Sayanarayana, R.: Associate relationship of concepts as seen through citations and citation index (1982)
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Rousseau, R.: Timelines in citation research (2006)
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Castro, R. de; Grossmann, J.W.: Famous trails to Paul Erdös (1999)
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-
Milman, B.L.: Individual co-citation clusters as nuclei of complete and dynamic informetric models of scientific and technological areas (1994)
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- Abstract
- Describes the construction of improved informetric models of individual scientific and technological areas on the basis of individual co citation clusters. The developed methodology of replenishment of research front with accidently absent papers describes the model more completely. Proposes the simple method of cluster 'dynamization' for the study of evolution of research area. The transition under consideration from co citation clusters to lexical maps of papers and patents enables the monitoring of the relationshuip between R and D in a given technological area. Provides the example from modern chemical engineering of Pressure-Swing Adsorption
-
Wagner-Döbler, R.: ¬Die Nutzung von Zitationsindizes durch deutsche Soziologen : Ergebnisse einer Umfrage (2001)
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-
Brooks, T.A.: How good are the best papers of JASIS? (2000)
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- Content
- Top by numbers of citations: (1) Saracevic, T. et al.: A study of information seeking and retrieving I-III (1988); (2) Bates, M.: Information search tactics (1979); (3) Cooper, W.S.: On selecting a measure of retrieval effectiveness (1973); (4) Marcus, R.S.: A experimental comparison of the effectiveness of computers and humans as search intermediaries (1983); (4) Fidel, R.: Online searching styles (1984)
-
Chen, C.; Cribbin, T.; Macredie, R.; Morar, S.: Visualizing and tracking the growth of competing paradigms : two case studies (2002)
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-
New Web Citation Index (2004)
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- Abstract
- Philadelphia, PA USA-London UK-Princeton, NJ February, 25, 2004 - Today, Thomson ISI and NEC Laboratories America (NEC) announced their collaboration to create a comprehensive, multidisciplinary citation index for Web-based scholarly resources. The new Web Citation Index(tm) will combine a suite of technologies developed by NEC, including "autonomous citation indexing" tools from NEC's CiteSeer environment, with the capabilities underlying ISI Web of KnowledgeSM. Thomson ISI editors will carefully monitor the quality of this new resource to ensure all indexed material meets the Thomson ISI high-quality standards. During 2004, Thomson ISI and NEC will operate a pilot of the new resource to receive feedback from the scientific and scholarly community. Full access to the index is projected for early 2005. When fully operational, the new resource will be a unique content collection within ISI Web of Knowledge. It will complement the Thomson ISI Web of Science(r), and provide researchers with a new gateway to discovery 4/3 using citation relationships among Web-based documents, such as pre-prints, proceedings, and "open access" research publications.
-
Frandsen, T.F.; Rousseau, R.: Article impact calculated over arbitrary periods (2005)
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Boyack, K.W.; Small, H.; Klavans, R.: Improving the accuracy of co-citation clustering using full text (2013)
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Hu, X.; Rousseau, R.: Do citation chimeras exist? : The case of under-cited influential articles suffering delayed recognition (2019)
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-
Stock, W.G.: Publikation und Zitat : Die problematische Basis empirischer Wissenschaftsforschung (2001)
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- Type
- r
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Rousseau, R.; Zuccala, A.: ¬A classification of author co-citations : definitions and search strategies (2004)
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Lai, K.-K.; Wu, S.-J.: Using the patent co-citation approach to establish a new patent classification system (2005)
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- Abstract
- The paper proposes a new approach to create a patent classification system to replace the IPC or UPC system for conducting patent analysis and management. The new approach is based on co-citation analysis of bibliometrics. The traditional approach for management of patents, which is based on either the IPC or UPC, is too general to meet the needs of specific industries. In addition, some patents are placed in incorrect categories, making it difficult for enterprises to carry out R&D planning, technology positioning, patent strategy-making and technology forecasting. Therefore, it is essential to develop a patent classification system that is adaptive to the characteristics of a specific industry. The analysis of this approach is divided into three phases. Phase I selects appropriate databases to conduct patent searches according to the subject and objective of this study and then select basic patents. Phase II uses the co-cited frequency of the basic patent pairs to assess their similarity. Phase III uses factor analysis to establish a classification system and assess the efficiency of the proposed approach. The main contribution of this approach is to develop a patent classification system based on patent similarities to assist patent manager in understanding the basic patents for a specific industry, the relationships among categories of technologies and the evolution of a technology category.
-
Klitzing, N.; Hoekstra, R.; Strijbos, J.-W,: Literature practices : processes leading up to a citation (2019)
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Safder, I.; Ali, M.; Aljohani, N.R.; Nawaz, R.; Hassan, S.-U.: Neural machine translation for in-text citation classification (2023)
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Czepel, R.: ¬Die Geographie der wissenschaftlichen Zitierung (2003)
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