-
Lorentzen, D.G.: Bridging polarised Twitter discussions : the interactions of the users in the middle (2021)
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- Date
- 20. 1.2015 18:30:22
12. 3.2021 18:45:15
-
Hayer, L.: Lazarsfeld zitiert : eine bibliometrische Analyse (2008)
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- Date
- 22. 6.2008 12:54:12
-
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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- Date
- 22. 1.2011 12:51:07
-
Walters, W.H.; Linvill, A.C.: Bibliographic index coverage of open-access journals in six subject areas (2011)
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- Abstract
- We investigate the extent to which open-access (OA) journals and articles in biology, computer science, economics, history, medicine, and psychology are indexed in each of 11 bibliographic databases. We also look for variations in index coverage by journal subject, journal size, publisher type, publisher size, date of first OA issue, region of publication, language of publication, publication fee, and citation impact factor. Two databases, Biological Abstracts and PubMed, provide very good coverage of the OA journal literature, indexing 60 to 63% of all OA articles in their disciplines. Five databases provide moderately good coverage (22-41%), and four provide relatively poor coverage (0-12%). OA articles in biology journals, English-only journals, high-impact journals, and journals that charge publication fees of $1,000 or more are especially likely to be indexed. Conversely, articles from OA publishers in Africa, Asia, or Central/South America are especially unlikely to be indexed. Four of the 11 databases index commercially published articles at a substantially higher rate than articles published by universities, scholarly societies, nonprofit publishers, or governments. Finally, three databases-EBSCO Academic Search Complete, ProQuest Research Library, and Wilson OmniFile-provide less comprehensive coverage of OA articles than of articles in comparable subscription journals.
-
Costas, R.; Zahedi, Z.; Wouters, P.: ¬The thematic orientation of publications mentioned on social media : large-scale disciplinary comparison of social media metrics with citations (2015)
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- Content
- Vgl.: https://doi.org/10.1108/AJIM-12-2014-0173.
- Date
- 20. 1.2015 18:30:22
-
Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020)
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- Date
- 20. 1.2015 18:30:22
12. 3.2021 18:41:28
-
Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023)
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- Date
- 22. 6.2023 18:07:12
-
Nicholls, P.T.: Empirical validation of Lotka's law (1986)
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- Source
- Information processing and management. 22(1986), S.417-419
-
Nicolaisen, J.: Citation analysis (2007)
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- Date
- 13. 7.2008 19:53:22
-
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
-
Diodato, V.: Dictionary of bibliometrics (1994)
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- Footnote
- Rez. in: Journal of library and information science 22(1996) no.2, S.116-117 (L.C. Smith)
-
Bookstein, A.: Informetric distributions : I. Unified overview (1990)
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- Date
- 22. 7.2006 18:55:29
-
Bookstein, A.: Informetric distributions : II. Resilience to ambiguity (1990)
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- Date
- 22. 7.2006 18:55:55
-
Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- Date
- 18. 3.2014 19:13:22
-
Shah, T.A.; Gul, S.; Gaur, R.C.: Authors self-citation behaviour in the field of Library and Information Science (2015)
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- Abstract
- Purpose The purpose of this paper is to analyse the author self-citation behavior in the field of Library and Information Science. Various factors governing the author self-citation behavior have also been studied. Design/methodology/approach The 2012 edition of Social Science Citation Index was consulted for the selection of LIS journals. Under the subject heading "Information Science and Library Science" there were 84 journals and out of these 12 journals were selected for the study based on systematic sampling. The study was confined to original research and review articles that were published in select journals in the year 2009. The main reason to choose 2009 was to get at least five years (2009-2013) citation data from Web of Science Core Collection (excluding Book Citation Index) and SciELO Citation Index. A citation was treated as self-citation whenever one of the authors of citing and cited paper was common, i.e., the set of co-authors of the citing paper and that of the cited one are not disjoint. To minimize the risk of homonyms, spelling variances and misspelling in authors' names, the authors compared full author names in citing and cited articles. Findings A positive correlation between number of authors and total number of citations exists with no correlation between number of authors and number/share of self-citations, i.e., self-citations are not affected by the number of co-authors in a paper. Articles which are produced in collaboration attract more self-citations than articles produced by only one author. There is no statistically significant variation in citations counts (total and self-citations) in works that are result of different types of collaboration. A strong and statistically significant positive correlation exists between total citation count and frequency of self-citations. No relation could be ascertained between total citation count and proportion of self-citations. Authors tend to cite more of their recent works than the work of other authors. Total citation count and number of self-citations are positively correlated with the impact factor of source publication and correlation coefficient for total citations is much higher than that for self-citations. A negative correlation exhibits between impact factor and the share of self-citations. Of particular note is that the correlation in all the cases is of weak nature. Research limitations/implications The research provides an understanding of the author self-citations in the field of LIS. readers are encouraged to further the study by taking into account large sample, tracing citations also from Book Citation Index (WoS) and comparing results with other allied subjects so as to validate the robustness of the findings of this study. Originality/value Readers are encouraged to further the study by taking into account large sample, tracing citations also from Book Citation Index (WoS) and comparing results with other allied subjects so as to validate the robustness of the findings of this study.
- Date
- 20. 1.2015 18:30:22
-
Narin, F.; Moll, J.K.: Bibliometrics (1977)
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- Source
- Annual review of information science and technology. 12(1977), S.35-58
-
Vinkler, P.: ¬A quasi-quantitative citation model (1987)
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