-
Prathap, G.: Fractionalized exergy for evaluating research performance (2011)
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- Abstract
- The approach based on "thermodynamic" considerations that can quantify research performance using an exergy term defined as X = iC, where i is the impact and C is the number of citations is now extended to cases where fractionalized counting of citations is used instead of integer counting.
-
Huang, M.-H.; Huang, W.-T.; Chang, C.-C.; Chen, D. Z.; Lin, C.-P.: The greater scattering phenomenon beyond Bradford's law in patent citation (2014)
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- Date
- 22. 8.2014 17:11:29
-
Campanario, J.M.: Large increases and decreases in journal impact factors in only one year : the effect of journal self-citations (2011)
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- Abstract
- I studied the factors (citations, self-citations, and number of articles) that influenced large changes in only 1 year in the impact factors (IFs) of journals. A set of 360 instances of journals with large increases or decreases in their IFs from a given year to the following was selected from journals in the Journal Citation Reports from 1998 to 2007 (40 journals each year). The main factor influencing large changes was the change in the number of citations. About 54% of the increases and 42% of the decreases in the journal IFs were associated with changes in the journal self-citations.
- Date
- 22. 1.2011 12:53:00
-
Schlögl, C.: Internationale Sichtbarkeit der europäischen und insbesondere der deutschsprachigen Informationswissenschaft (2013)
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- Date
- 22. 3.2013 14:04:09
-
Ajiferuke, I.; Lu, K.; Wolfram, D.: ¬A comparison of citer and citation-based measure outcomes for multiple disciplines (2010)
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- Date
- 28. 9.2010 12:54:22
-
Lamb, I.; Larson, C.: Shining a light on scientific data : building a data catalog to foster data sharing and reuse (2016)
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-
D'Angelo, C.A.; Giuffrida, C.; Abramo, G.: ¬A heuristic approach to author name disambiguation in bibliometrics databases for large-scale research assessments (2011)
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- Date
- 22. 1.2011 13:06:52
-
Leydesdorff, L.; Rafols, I.; Chen, C.: Interactive overlays of journals and the measurement of interdisciplinarity on the basis of aggregated journal-journal citations (2013)
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-
Ping, Q.; He, J.; Chen, C.: How many ways to use CiteSpace? : a study of user interactive events over 14 months (2017)
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- Abstract
- Using visual analytic systems effectively may incur a steep learning curve for users, especially for those who have little prior knowledge of either using the tool or accomplishing analytic tasks. How do users deal with a steep learning curve over time? Are there particularly problematic aspects of an analytic process? In this article we investigate these questions through an integrative study of the use of CiteSpace-a visual analytic tool for finding trends and patterns in scientific literature. In particular, we analyze millions of interactive events in logs generated by users worldwide over a 14-month period. The key findings are: (i) three levels of proficiency are identified, namely, level 1: low proficiency, level 2: intermediate proficiency, and level 3: high proficiency, and (ii) behavioral patterns at level 3 are resulted from a more engaging interaction with the system, involving a wider variety of events and being characterized by longer state transition paths, whereas behavioral patterns at levels 1 and 2 seem to focus on learning how to use the tool. This study contributes to the development and evaluation of visual analytic systems in realistic settings and provides a valuable addition to the study of interactive visual analytic processes.
-
Norris, M.; Oppenheim, C.: ¬The h-index : a broad review of a new bibliometric indicator (2010)
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- Date
- 8. 1.2011 19:22:13
-
Leydesdorff, L.; Bornmann, L.: How fractional counting of citations affects the impact factor : normalization in terms of differences in citation potentials among fields of science (2011)
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- Abstract
- The Impact Factors (IFs) of the Institute for Scientific Information suffer from a number of drawbacks, among them the statistics-Why should one use the mean and not the median?-and the incomparability among fields of science because of systematic differences in citation behavior among fields. Can these drawbacks be counteracted by fractionally counting citation weights instead of using whole numbers in the numerators? (a) Fractional citation counts are normalized in terms of the citing sources and thus would take into account differences in citation behavior among fields of science. (b) Differences in the resulting distributions can be tested statistically for their significance at different levels of aggregation. (c) Fractional counting can be generalized to any document set including journals or groups of journals, and thus the significance of differences among both small and large sets can be tested. A list of fractionally counted IFs for 2008 is available online at http:www.leydesdorff.net/weighted_if/weighted_if.xls The between-group variance among the 13 fields of science identified in the U.S. Science and Engineering Indicators is no longer statistically significant after this normalization. Although citation behavior differs largely between disciplines, the reflection of these differences in fractionally counted citation distributions can not be used as a reliable instrument for the classification.
- Date
- 22. 1.2011 12:51:07
-
Schubert, T.; Michels, C.: Placing articles in the large publisher nations : is there a "free lunch" in terms of higher impact? (2013)
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- Date
- 22. 3.2013 19:45:49
-
Liu, S.; Chen, C.: ¬The differences between latent topics in abstracts and citation contexts of citing papers (2013)
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- Date
- 22. 3.2013 19:50:00
-
Kuan, C.-H.; Liu, J.S.: ¬A new approach for main path analysis : decay in knowledge diffusion (2016)
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- Date
- 22. 1.2016 14:23:00
-
Epifanio, I.: Mapping the asymmetrical citation relationships between journals by h-plots (2014)
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- Abstract
- I propose the use of h-plots for visualizing the asymmetric relationships between the citing and cited profiles of journals in a common map. With this exploratory tool, we can understand better the journal's dual roles of citing and being cited in a reference network. The h-plot is introduced and its use is validated with a set of 25 journals belonging to the statistics area. The relatedness factor is considered for describing the relations of citations from a journal "i" to a journal "j," and the citations from the journal "j" to the journal "i." More information has been extracted from the h-plot, compared with other statistical techniques for modelling and representing asymmetric data, such as multidimensional unfolding.
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Abbasi, M. K.; Frommholz, I.: Cluster-based polyrepresentation as science modelling approach for information retrieval (2015)
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-
Haustein, S.: Scientific interactions and research evaluation : from bibliometrics to Altmetrics (2015)
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- Source
- Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff
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Lewandowski, D.; Haustein, S.: What does the German-language information science community cite? (2015)
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- Source
- Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff
-
Schreiber, M.: Do we need the g-index? (2013)
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- Abstract
- Using a very small sample of 8 data sets it was recently shown by De Visscher (2011) that the g-index is very close to the square root of the total number of citations. It was argued that there is no bibliometrically meaningful difference. Using another somewhat larger empirical sample of 26 data sets I show that the difference may be larger and I argue in favor of the g-index.
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Milard, B.: ¬The social circles behind scientific references : relationships between citing and cited authors in chemistry publications (2014)
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- Abstract
- This paper provides a better understanding of the implications of researchers' social networks in bibliographic references. Using a set of chemistry papers and conducting interviews with their authors (n = 32), I characterize the type of relation the author has with the authors of the references contained in his/her paper (n = 3,623). I show that citation relationships do not always involve underlying personal exchanges and that unknown references are an essential component, revealing segmentations in scientific groups. The relationships implied by references are of various strengths and origins. Several inclusive social circles are then identified: co-authors, close acquaintances, colleagues, invisible colleges, peers, contactables, and strangers. I conclude that publication is a device that contributes to a relatively stable distribution among the various social circles that structure scientific sociability.
