Search (74 results, page 2 of 4)

  • × theme_ss:"Informetrie"
  • × year_i:[2010 TO 2020}
  1. Xu, F.; Liu, W.B.; Mingers, J.: New journal classification methods based on the global h-index (2015) 0.02
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    Abstract
    In this work we develop new journal classification methods based on the h-index. The introduction of the h-index for research evaluation has attracted much attention in the bibliometric study and research quality evaluation. The main purpose of using an h-index is to compare the index for different research units (e.g. researchers, journals, etc.) to differentiate their research performance. However the h-index is defined by only comparing citations counts of one's own publications, it is doubtful that the h index alone should be used for reliable comparisons among different research units, like researchers or journals. In this paper we propose a new global h-index (Gh-index), where the publications in the core are selected in comparison with all the publications of the units to be evaluated. Furthermore, we introduce some variants of the Gh-index to address the issue of discrimination power. We show that together with the original h-index, they can be used to evaluate and classify academic journals with some distinct advantages, in particular that they can produce an automatic classification into a number of categories without arbitrary cut-off points. We then carry out an empirical study for classification of operations research and management science (OR/MS) journals using this index, and compare it with other well-known journal ranking results such as the Association of Business Schools (ABS) Journal Quality Guide and the Committee of Professors in OR (COPIOR) ranking lists.
  2. Gazni, A.; Ghaseminik, Z.: Author practices in citing other authors, institutions, and journals (2016) 0.02
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    Abstract
    This study explores the extent to which authors with different impact and productivity levels cite journals, institutions, and other authors through an analysis of the scientific papers of 37,717 authors during 1990-2013. The results demonstrate that the core-scatter distribution of cited authors, institutions, and journals varies for authors in each impact and productivity class. All authors in the science network receive the majority of their credit from high-impact authors; however, this effect decreases as authors' impact levels decrease. Similarly, the proportion of citations that lower-impact authors make to each other increases as authors' impact levels decrease. High-impact authors, who have the highest degree of membership in the science network, publish fewer papers in comparison to highly productive authors. However, authors with the highest impact make both more references per paper and also more citations to papers in the science network. This suggests that high-impact authors produce the most relevant work in the science network. Comparing practices by productivity level, authors receive the majority of their credit from highly productive authors and authors cite highly productive authors more frequently than less productive authors.
  3. Leydesdorff, L.; Wagner, C.S.; Porto-Gomez, I.; Comins, J.A.; Phillips, F.: Synergy in the knowledge base of U.S. innovation systems at national, state, and regional levels : the contributions of high-tech manufacturing and knowledge-intensive services (2019) 0.02
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    Abstract
    Using information theory, we measure innovation systemness as synergy among size-classes, ZIP Codes, and technological classes (NACE-codes) for 8.5 million American companies. The synergy at the national level is decomposed at the level of states, Core-Based Statistical Areas (CBSA), and Combined Statistical Areas (CSA). We zoom in to the state of California and in more detail to Silicon Valley. Our results do not support the assumption of a national system of innovations in the U.S.A. Innovation systems appear to operate at the level of the states; the CBSA are too small, so that systemness spills across their borders. Decomposition of the sample in terms of high-tech manufacturing (HTM), medium-high-tech manufacturing (MHTM), knowledge-intensive services (KIS), and high-tech services (HTKIS) does not change this pattern, but refines it. The East Coast-New Jersey, Boston, and New York-and California are the major players, with Texas a third one in the case of HTKIS. Chicago and industrial centers in the Midwest also contribute synergy. Within California, Los Angeles contributes synergy in the sectors of manufacturing, the San Francisco area in KIS. KIS in Silicon Valley and the Bay Area-a CSA composed of seven CBSA-spill over to other regions and even globally.
  4. Bensman, S.J.; Smolinsky, L.J.; Pudovkin, A.I.: Mean citation rate per article in mathematics journals : differences from the scientific model (2010) 0.01
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    Abstract
    This paper analyzes the applicability of the article mean citation rate measures in the Science Citation Index Journal Citation Reports (SCI JCR) to the five JCR mathematical subject categories. These measures are the traditional 2-year impact factor as well as the recently added 5-year impact factor and 5-year article influence score. Utilizing the 2008 SCI JCR, the paper compares the probability distributions of the measures in the mathematical categories to the probability distribution of a scientific model of impact factor distribution. The scientific model distribution is highly skewed, conforming to the negative binomial type, with much of the variance due to the important role of review articles in science. In contrast, the three article mean citation rate measures' distributions in the mathematical categories conformed to either the binomial or Poisson, indicating a high degree of randomness. Seeking reasons for this, the paper analyzes the bibliometric structure of Mathematics, finding it a disjointed discipline of isolated subfields with a weak central core of journals, reduced review function, and long cited half-life placing most citations beyond the measures' time limits. These combine to reduce the measures' variance to one commensurate with random error. However, the measures were found capable of identifying important journals. Using data from surveys of the Louisiana State University (LSU) faculty, the paper finds a higher level of consensus among mathematicians and others on which are the important mathematics journals than the measures indicate, positing that much of the apparent randomness may be due to the measures' inapplicability to mathematical disciplines. Moreover, tests of the stability of impact factor ranks across a 5-year time span suggested that the proper model for Mathematics is the negative binomial.
  5. Scholarly metrics under the microscope : from citation analysis to academic auditing (2015) 0.01
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    Date
    22. 1.2017 17:12:50
  6. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.01
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    Date
    22. 8.2014 17:05:18
  7. Ohly, P.: Dimensions of globality : a bibliometric analysis (2016) 0.01
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    Date
    20. 1.2019 11:22:31
  8. 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) 0.01
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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.
  9. Yan, E.: Finding knowledge paths among scientific disciplines (2014) 0.01
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    Date
    26.10.2014 20:22:22
  10. Campanario, J.M.: Large increases and decreases in journal impact factors in only one year : the effect of journal self-citations (2011) 0.01
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    Date
    22. 1.2011 12:53:00
  11. Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.01
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    Date
    22. 1.2011 13:02:21
  12. Schlögl, C.: Internationale Sichtbarkeit der europäischen und insbesondere der deutschsprachigen Informationswissenschaft (2013) 0.01
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    Date
    22. 3.2013 14:04:09
  13. 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) 0.01
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    Date
    18. 3.2014 18:22:21
  14. Ajiferuke, I.; Lu, K.; Wolfram, D.: ¬A comparison of citer and citation-based measure outcomes for multiple disciplines (2010) 0.01
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    Date
    28. 9.2010 12:54:22
  15. Albarrán, P.; Ruiz-Castillo, J.: References made and citations received by scientific articles (2011) 0.01
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    Abstract
    This article studies massive evidence about references made and citations received after a 5-year citation window by 3.7 million articles published in 1998 to 2002 in 22 scientific fields. We find that the distributions of references made and citations received share a number of basic features across sciences. Reference distributions are rather skewed to the right while citation distributions are even more highly skewed: The mean is about 20 percentage points to the right of the median, and articles with a remarkable or an outstanding number of citations represent about 9% of the total. Moreover, the existence of a power law representing the upper tail of citation distributions cannot be rejected in 17 fields whose articles represent 74.7% of the total. Contrary to the evidence in other contexts, the value of the scale parameter is above 3.5 in 13 of the 17 cases. Finally, power laws are typically small, but capture a considerable proportion of the total citations received.
  16. D'Angelo, C.A.; Giuffrida, C.; Abramo, G.: ¬A heuristic approach to author name disambiguation in bibliometrics databases for large-scale research assessments (2011) 0.01
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    Date
    22. 1.2011 13:06:52
  17. Hicks, D.; Wang, J.: Coverage and overlap of the new social sciences and humanities journal lists (2011) 0.01
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    Date
    22. 1.2011 13:21:28
  18. Jovanovic, M.: ¬Eine kleine Frühgeschichte der Bibliometrie (2012) 0.01
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    Date
    22. 7.2012 19:23:32
  19. ¬Die deutsche Zeitschrift für Dokumentation, Informationswissenschaft und Informationspraxis von 1950 bis 2011 : eine vorläufige Bilanz in vier Abschnitten (2012) 0.01
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    Date
    22. 7.2012 19:35:26
  20. Frandsen, T.F.; Nicolaisen, J.: ¬The ripple effect : citation chain reactions of a nobel prize (2013) 0.01
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    Date
    22. 3.2013 16:21:09

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