Search (95 results, page 2 of 5)

  • × theme_ss:"Informetrie"
  • × year_i:[2010 TO 2020}
  1. 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
  2. Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.01
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    Date
    22. 1.2011 13:02:21
  3. 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
  4. 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
  5. Aksnes, D.W.; Rorstad, K.; Piro, F.; Sivertsen, G.: Are female researchers less cited? : a large-scale study of Norwegian scientists (2011) 0.01
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  6. Dalen, H.P. van; Henkens, K.: Intended and unintended consequences of a publish-or-perish culture : a worldwide survey (2012) 0.01
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  7. Larivière, V.; Gingras, Y.: ¬The impact factor's Matthew Effect : a natural experiment in bibliometrics (2010) 0.01
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    Abstract
    Since the publication of Robert K. Merton's theory of cumulative advantage in science (Matthew Effect), several empirical studies have tried to measure its presence at the level of papers, individual researchers, institutions, or countries. However, these studies seldom control for the intrinsic quality of papers or of researchers - better (however defined) papers or researchers could receive higher citation rates because they are indeed of better quality. Using an original method for controlling the intrinsic value of papers - identical duplicate papers published in different journals with different impact factors - this paper shows that the journal in which papers are published have a strong influence on their citation rates, as duplicate papers published in high-impact journals obtain, on average, twice as many citations as their identical counterparts published in journals with lower impact factors. The intrinsic value of a paper is thus not the only reason a given paper gets cited or not, there is a specific Matthew Effect attached to journals and this gives to papers published there an added value over and above their intrinsic quality.
  8. Ahlgren, P.; Järvelin, K.: Measuring impact of twelve information scientists using the DCI index (2010) 0.01
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  9. Jonkers, K.; Derrick, G.E.: ¬The bibliometric bandwagon : characteristics of bibliometric articles outside the field literature (2012) 0.01
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  10. Jonkers, K.; Moya Anegon, F. de; Aguillo, I.F.: Measuring the usage of e-research infrastructure as an indicator of research activity (2012) 0.01
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  11. Moohebat, M.; Raj, R.G.; Kareem, S.B.A.; Thorleuchter, D.: Identifying ISI-indexed articles by their lexical usage : a text analysis approach (2015) 0.01
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    Abstract
    This research creates an architecture for investigating the existence of probable lexical divergences between articles, categorized as Institute for Scientific Information (ISI) and non-ISI, and consequently, if such a difference is discovered, to propose the best available classification method. Based on a collection of ISI- and non-ISI-indexed articles in the areas of business and computer science, three classification models are trained. A sensitivity analysis is applied to demonstrate the impact of words in different syntactical forms on the classification decision. The results demonstrate that the lexical domains of ISI and non-ISI articles are distinguishable by machine learning techniques. Our findings indicate that the support vector machine identifies ISI-indexed articles in both disciplines with higher precision than do the Naïve Bayesian and K-Nearest Neighbors techniques.
  12. Chang, K.-C.; Zhou, W.; Zhang, S.; Yuan, C,-C.: Threshold effects of the patent H-index in the relationship between patent citations and market value (2015) 0.01
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  13. Haustein, S.; Bowman, T.D.; Holmberg, K.; Tsou, A.; Sugimoto, C.R.; Larivière, V.: Tweets as impact indicators : Examining the implications of automated "bot" accounts on Twitter (2016) 0.01
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  14. Kousha, K.; Thelwall, M.: Can Amazon.com reviews help to assess the wider impacts of books? (2016) 0.01
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  15. Orduna-Malea, E.; Thelwall, M.; Kousha, K.: Web citations in patents : evidence of technological impact? (2017) 0.01
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  16. Zhao, M.; Yan, E.; Li, K.: Data set mentions and citations : a content analysis of full-text publications (2018) 0.01
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  17. 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.
  18. 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
  19. 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
  20. Jovanovic, M.: ¬Eine kleine Frühgeschichte der Bibliometrie (2012) 0.01
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    Date
    22. 7.2012 19:23:32

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