Search (64 results, page 1 of 4)

  • × theme_ss:"Informetrie"
  • × type_ss:"a"
  • × year_i:[2010 TO 2020}
  1. Herb, U.; Beucke, D.: ¬Die Zukunft der Impact-Messung : Social Media, Nutzung und Zitate im World Wide Web (2013) 0.31
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    Content
    Vgl. unter: https://www.leibniz-science20.de%2Fforschung%2Fprojekte%2Faltmetrics-in-verschiedenen-wissenschaftsdisziplinen%2F&ei=2jTgVaaXGcK4Udj1qdgB&usg=AFQjCNFOPdONj4RKBDf9YDJOLuz3lkGYlg&sig2=5YI3KWIGxBmk5_kv0P_8iQ.
  2. Frandsen, T.F.; Nicolaisen, J.: Citation behavior : a large-scale test of the persuasion by name-dropping hypothesis (2017) 0.02
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    Abstract
    Citation frequencies are commonly interpreted as measures of quality or impact. Yet, the true nature of citations and their proper interpretation have been the center of a long, but still unresolved discussion in Bibliometrics. A comparison of 67,578 pairs of studies on the same healthcare topic, with the same publication age (1-15 years) reveals that when one of the studies is being selected for citation, it has on average received about three times as many citations as the other study. However, the average citation-gap between selected or deselected studies narrows slightly over time, which fits poorly with the name-dropping interpretation and better with the quality and impact-interpretation. The results demonstrate that authors in the field of Healthcare tend to cite highly cited documents when they have a choice. This is more likely caused by differences related to quality than differences related to status of the publications cited.
  3. Waltman, L.; Calero-Medina, C.; Kosten, J.; Noyons, E.C.M.; Tijssen, R.J.W.; Eck, N.J. van; Leeuwen, T.N. van; Raan, A.F.J. van; Visser, M.S.; Wouters, P.: ¬The Leiden ranking 2011/2012 : data collection, indicators, and interpretation (2012) 0.01
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    Abstract
    The Leiden Ranking 2011/2012 is a ranking of universities based on bibliometric indicators of publication output, citation impact, and scientific collaboration. The ranking includes 500 major universities from 41 different countries. This paper provides an extensive discussion of the Leiden Ranking 2011/2012. The ranking is compared with other global university rankings, in particular the Academic Ranking of World Universities (commonly known as the Shanghai Ranking) and the Times Higher Education World University Rankings. The comparison focuses on the methodological choices underlying the different rankings. Also, a detailed description is offered of the data collection methodology of the Leiden Ranking 2011/2012 and of the indicators used in the ranking. Various innovations in the Leiden Ranking 2011/2012 are presented. These innovations include (1) an indicator based on counting a university's highly cited publications, (2) indicators based on fractional rather than full counting of collaborative publications, (3) the possibility of excluding non-English language publications, and (4) the use of stability intervals. Finally, some comments are made on the interpretation of the ranking and a number of limitations of the ranking are pointed out.
  4. Riviera, E.: Testing the strength of the normative approach in citation theory through relational bibliometrics : the case of Italian sociology (2015) 0.01
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    Abstract
    In scientometrics, citer behavior is traditionally investigated using one of two main approaches. According to the normative point of view, the behavior of scientists is regulated by norms that make the detection of citation patterns useful for the interpretation of bibliometric measures. According to the constructivist perspective, citer behavior is influenced by other factors linked to the social and/or psychological sphere that do not allow any statistical inferences that are useful for the purposes of interpretation. An intermediate position supports normative theories in describing citer behavior with respect to high citation frequencies and constructivist theories with respect to low citation counts. In this paper, this idea was tested in a case study of the Italian sociology community. Italian sociology is characterized by an unusual organization into three "political" or "ideological" camps, and belonging to one camp can be considered a potentially strong constructivist reason to cite. An all-author co-citation analysis was performed to map the structure of the Italian sociology community and look for evidence of three camps. We did not expect to find evidence of this configuration in the co-citation map. The map, in fact, included authors who obtained high citation counts that are supposedly produced by a normative-oriented behavior. The results confirmed this hypothesis and showed that the clusters seemed to be divided according to topic and not by camp. Relevant scientific works were cited by the members of the entire community regardless of their membership in any particular camp.
  5. Chen, C.; Ibekwe-SanJuan, F.; Hou, J.: ¬The structure and dynamics of cocitation clusters : a multiple-perspective cocitation analysis (2010) 0.01
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    Abstract
    A multiple-perspective cocitation analysis method is introduced for characterizing and interpreting the structure and dynamics of cocitation clusters. The method facilitates analytic and sense making tasks by integrating network visualization, spectral clustering, automatic cluster labeling, and text summarization. Cocitation networks are decomposed into cocitation clusters. The interpretation of these clusters is augmented by automatic cluster labeling and summarization. The method focuses on the interrelations between a cocitation cluster's members and their citers. The generic method is applied to a three-part analysis of the field of information science as defined by 12 journals published between 1996 and 2008: (a) a comparative author cocitation analysis (ACA), (b) a progressive ACA of a time series of cocitation networks, and (c) a progressive document cocitation analysis (DCA). Results show that the multiple-perspective method increases the interpretability and accountability of both ACA and DCA networks.
  6. Zhao, D.; Strotmann, A.: In-text author citation analysis : feasibility, benefits, and limitations (2014) 0.01
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    Abstract
    This article explores the feasibility, benefits, and limitations of in-text author citation analysis and tests how well it works compared with traditional author citation analysis using citation databases. In-text author citation analysis refers to author-based citation analysis using in-text citation data from full-text articles rather than reference data from citation databases. It has the potential to help with the application of citation analysis to research fields such as the social sciences that are not covered well by citation databases and to support weighted citation and cocitation counting for improved citation analysis results. We found that in-text author citation analysis can work as well as traditional citation analysis using citation databases for both author ranking and mapping if author name disambiguation is performed properly. Using in-text citation data without any author name disambiguation, ranking authors by citations is useless, whereas cocitation analysis works well for identifying major specialties and their interrelationships with cautions required for the interpretation of small research areas and some authors' memberships in specialties.
  7. Bornmann, L.; Moya Anegón, F.de: What proportion of excellent papers makes an institution one of the best worldwide? : Specifying thresholds for the interpretation of the results of the SCImago Institutions Ranking and the Leiden Ranking (2014) 0.01
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  8. Ye, F.Y.; Leydesdorff, L.: ¬The "academic trace" of the performance matrix : a mathematical synthesis of the h-index and the integrated impact indicator (I3) (2014) 0.01
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    Abstract
    The h-index provides us with 9 natural classes which can be written as a matrix of 3 vectors. The 3 vectors are: X = (X1, X2, X3) and indicates publication distribution in the h-core, the h-tail, and the uncited ones, respectively; Y = (Y1, Y2, Y3) denotes the citation distribution of the h-core, the h-tail and the so-called "excess" citations (above the h-threshold), respectively; and Z = (Z1, Z2, Z3) = (Y1-X1, Y2-X2, Y3-X3). The matrix V = (X,Y,Z)T constructs a measure of academic performance, in which the 9 numbers can all be provided with meanings in different dimensions. The "academic trace" tr(V) of this matrix follows naturally, and contributes a unique indicator for total academic achievements by summarizing and weighting the accumulation of publications and citations. This measure can also be used to combine the advantages of the h-index and the integrated impact indicator (I3) into a single number with a meaningful interpretation of the values. We illustrate the use of tr(V) for the cases of 2 journal sets, 2 universities, and ourselves as 2 individual authors.
  9. Mohammadi, E.; Thelwall, M.; Kousha, K.: Can Mendeley bookmarks reflect readership? : a survey of user motivations (2016) 0.01
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    Abstract
    Although Mendeley bookmarking counts appear to correlate moderately with conventional citation metrics, it is not known whether academic publications are bookmarked in Mendeley in order to be read or not. Without this information, it is not possible to give a confident interpretation of altmetrics derived from Mendeley. In response, a survey of 860 Mendeley users shows that it is reasonable to use Mendeley bookmarking counts as an indication of readership because most (55%) users with a Mendeley library had read or intended to read at least half of their bookmarked publications. This was true across all broad areas of scholarship except for the arts and humanities (42%). About 85% of the respondents also declared that they bookmarked articles in Mendeley to cite them in their publications, but some also bookmark articles for use in professional (50%), teaching (25%), and educational activities (13%). Of course, it is likely that most readers do not record articles in Mendeley and so these data do not represent all readers. In conclusion, Mendeley bookmark counts seem to be indicators of readership leading to a combination of scholarly impact and wider professional impact.
  10. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.00
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    Date
    18. 3.2014 19:13:22
  11. Herb, U.: Relevanz von Impact-Maßen für Open Access (2013) 0.00
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    Abstract
    Die Anwendung bibliometrischer Verfahren ist sowohl für Wissenschaftler als auch für Organisationen höchst relevant: Individuelle Karriere und Evaluierung von Fachbereichen sind abhängig von der Bewertung des Publikationsverhaltens. Der Beitrag eruiert, warum Open-Access-Publikationen in solchen Bewertungen benachteiligt werden, wie die in der Evaluierung üblicherweise herangezogenen bibliometrischen Verfahren (v.a. der Journal impact Factor JIF) funktionieren, welche Alternativen zu diesen zitationsbasierten Verfahren existieren und zu welchen Ergebnissen sie kommen. Unter der Annahme, dass Open-Access-Publikationen nicht qua geringer Qualität geringere Wertschätzung in der Evaluierung und bei Berufungskommissionen erfahren, sondern aufgrund methodischer Eigenheiten der Evaluierungsinstrumente, wird diskutiert, inwiefern alternative Qualitätsmessungsverfahren sich vorteilhaft auf die Akzeptanz von Open Access auswirken können.
  12. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.00
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    Date
    22. 8.2014 17:05:18
  13. Ohly, P.: Dimensions of globality : a bibliometric analysis (2016) 0.00
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    Date
    20. 1.2019 11:22:31
  14. Crespo, J.A.; Herranz, N.; Li, Y.; Ruiz-Castillo, J.: ¬The effect on citation inequality of differences in citation practices at the web of science subject category level (2014) 0.00
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    Abstract
    This article studies the impact of differences in citation practices at the subfield, or Web of Science subject category level, using the model introduced in Crespo, Li, and Ruiz-Castillo (2013a), according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters data set of about 4.4 million articles used in Crespo et al. (2013a) to analyze 22 broad fields. The main results are the following: First, when the classification system goes from 22 fields to 219 subfields the effect on citation inequality of differences in citation practices increases from ?14% at the field level to 18% at the subfield level. Second, we estimate a set of exchange rates (ERs) over a wide [660, 978] citation quantile interval to express the citation counts of articles into the equivalent counts in the all-sciences case. In the fractional case, for example, we find that in 187 of 219 subfields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. Third, in the fractional case the normalization of the raw data using the ERs (or subfield mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourth, the results in the fractional case are essentially replicated when we adopt a multiplicative approach.
  15. Yan, E.: Finding knowledge paths among scientific disciplines (2014) 0.00
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    Date
    26.10.2014 20:22:22
  16. Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015) 0.00
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    Date
    20. 1.2015 18:30:22
    17. 9.2018 18:22:23
  17. Campanario, J.M.: Large increases and decreases in journal impact factors in only one year : the effect of journal self-citations (2011) 0.00
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    Date
    22. 1.2011 12:53:00
  18. Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.00
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  19. Schlögl, C.: Internationale Sichtbarkeit der europäischen und insbesondere der deutschsprachigen Informationswissenschaft (2013) 0.00
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  20. Vieira, E.S.; Cabral, J.A.S.; Gomes, J.A.N.F.: Definition of a model based on bibliometric indicators for assessing applicants to academic positions (2014) 0.00
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