Search (193 results, page 1 of 10)

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Abstract

In both the social sciences and the humanities, books and monographs play significant roles in research communication. The absence of citations from most books and monographs from the Thomson Reuters/Institute for Scientific Information databases (ISI) has been criticized, but attempts to include citations from or to books in the research evaluation of the social sciences and humanities have not led to widespread adoption. This article assesses whether Google Book Search (GBS) can partially fill this gap by comparing citations from books with citations from journal articles to journal articles in 10 science, social science, and humanities disciplines. Book citations were 31% to 212% of ISI citations and, hence, numerous enough to supplement ISI citations in the social sciences and humanities covered, but not in the sciences (3%-5%), except for computing (46%), due to numerous published conference proceedings. A case study was also made of all 1,923 articles in the 51 information science and library science ISI-indexed journals published in 2003. Within this set, highly book-cited articles tended to receive many ISI citations, indicating a significant relationship between the two types of citation data, but with important exceptions that point to the additional information provided by book citations. In summary, GBS is clearly a valuable new source of citation data for the social sciences and humanities. One practical implication is that book-oriented scholars should consult it for additional citations to their work when applying for promotion and tenure.

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.8, S.1537-1549

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Abstract

We use a new data gathering method, "Web/URL citation," Web/URL and Google Scholar to compare traditional and Web-based citation patterns across multiple disciplines (biology, chemistry, physics, computing, sociology, economics, psychology, and education) based upon a sample of 1,650 articles from 108 open access (OA) journals published in 2001. A Web/URL citation of an online journal article is a Web mention of its title, URL, or both. For each discipline, except psychology, we found significant correlations between Thomson Scientific (formerly Thomson ISI, here: ISI) citations and both Google Scholar and Google Web/URL citations. Google Scholar citations correlated more highly with ISI citations than did Google Web/URL citations, indicating that the Web/URL method measures a broader type of citation phenomenon. Google Scholar citations were more numerous than ISI citations in computer science and the four social science disciplines, suggesting that Google Scholar is more comprehensive for social sciences and perhaps also when conference articles are valued and published online. We also found large disciplinary differences in the percentage overlap between ISI and Google Scholar citation sources. Finally, although we found many significant trends, there were also numerous exceptions, suggesting that replacing traditional citation sources with the Web or Google Scholar for research impact calculations would be problematic.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.7, S.1055-1065

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Abstract

How do authors refer to Web-based information sources in their formal scientific publications? It is not yet weIl known how scientists and scholars actually include new types of information sources, available through the new media, in their published work. This article reports an a comparative study of the lists of references in 38 scientific journals in five different scientific and social scientific fields. The fields are sociology, library and information science, biochemistry and biotechnology, neuroscience, and the mathematics of computing. As is weIl known, references, citations, and hyperlinks play different roles in academic publishing and communication. Our study focuses an hyperlinks as attributes of references in formal scholarly publications. The study developed and applied a method to analyze the differential roles of publishing media in the analysis of scientific and scholarly literature references. The present secondary databases that include reference and citation data (the Web of Science) cannot be used for this type of research. By the automated processing and analysis of the full text of scientific and scholarly articles, we were able to extract the references and hyperlinks contained in these references in relation to other features of the scientific and scholarly literature. Our findings show that hyperlinking references are indeed, as expected, abundantly present in the formal literature. They also tend to cite more recent literature than the average reference. The large majority of the references are to Web instances of traditional scientific journals. Other types of Web-based information sources are less weIl represented in the lists of references, except in the case of pure e-journals. We conclude that this can be explained by taking the role of the publisher into account. Indeed, it seems that the shift from print-based to electronic publishing has created new roles for the publisher. By shaping the way scientific references are hyperlinking to other information sources, the publisher may have a large impact an the availability of scientific and scholarly information.

Source

Journal of the American Society for Information Science and Technology. 55(2004) no.14, S.1250-1260

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Abstract

This article challenges recent research (Evans, 2008) reporting that the concentration of cited scientific literature increases with the online availability of articles and journals. Using Thomson Reuters' Web of Science, the present article analyses changes in the concentration of citations received (2- and 5-year citation windows) by papers published between 1900 and 2005. Three measures of concentration are used: the percentage of papers that received at least one citation (cited papers); the percentage of papers needed to account for 20%, 50%, and 80% of the citations; and the Herfindahl-Hirschman index (HHI). These measures are used for four broad disciplines: natural sciences and engineering, medical fields, social sciences, and the humanities. All these measures converge and show that, contrary to what was reported by Evans, the dispersion of citations is actually increasing.

Date

22. 3.2009 19:22:35

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.858-862

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Abstract

The paper attempts to provide an alternative method for measuring the importance of scientific papers based on the Google's PageRank. The method is a meaningful extension of the common integer counting of citations and is then experimented for bringing PageRank to the citation analysis in a large citation network. It offers a more integrated picture of the publications' influence in a specific field. We firstly calculate the PageRanks of scientific papers. The distributional characteristics and comparison with the traditionally used number of citations are then analyzed in detail. Furthermore, the PageRank is implemented in the evaluation of research influence for several countries in the field of Biochemistry and Molecular Biology during the time period of 2000-2005. Finally, some advantages of bringing PageRank to the citation analysis are concluded.

Date

31. 7.2008 14:22:05

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Date

16.12.2001 14:01:22

Source

Journal of the American Society for Information Science and technology. 52(2001) no.14, S.1197-1202

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Date

22. 7.2006 15:20:01

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.3, S.330-341

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Abstract

Conclusion There is a reason why Google Scholar and Web of Science/Scopus are kings of the hills in their various arenas. They have strong brand recogniton, a head start in development and a mass of eyeballs and users that leads to an almost virtious cycle of improvement. Competing against such well established competitors is not easy even when one has deep pockets (Microsoft) or a killer idea (scite). It will be interesting to see how the landscape will look like in 2030. Stay tuned for part II where I review each particular index.

Date

17.11.2020 12:22:59

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Abstract

In this article a quantitative study is reported on the resistance that scientists may encounter when they do innovative work or when they attempt to publish articles that later become highly cited. A set of 205 commentaries by authors of some of the most-cited papers of all times have been examined in order to identify those articles whose authors encountered difficulty in getting his or her work published. There are 22 commentaries (10,7%) in which authors mention some difficulty or resistance in doing or publishing the research reported in the article. Three of the articles which had problems in being published are the most cited from their respective journals. According the authors' commentaries, although sometimes referees' negative evaluations can help improve the articles, in other instances referees and editors wrongly rejected the highly cited articles

Source

Journal of the American Society for Information Science. 47(1996) no.4, S.302-310

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Date

3. 1.2007 17:22:03

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.9, S.1263-1274

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Abstract

Citation rates are becoming increasingly important in judging the research quality of journals, institutions and departments, and individual faculty. This paper looks at the pattern of citations across different management science journals and over time. A stochastic model is proposed which views the generating mechanism of citations as a gamma mixture of Poisson processes generating overall a negative binomial distribution. This is tested empirically with a large sample of papers published in 1990 from six management science journals and found to fit well. The model is extended to include obsolescence, i.e., that the citation rate for a paper varies over its cited lifetime. This leads to the additional citations distribution which shows that future citations are a linear function of past citations with a time-dependent and decreasing slope. This is also verified empirically in a way that allows different obsolescence functions to be fitted to the data. Conclusions concerning the predictability of future citations, and future research in this area are discussed.

Date

26.12.2007 19:22:05

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Date

22. 8.2014 16:52:04

Source

Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1820-1833

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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

Source

Journal of the American Society for Information Science and technology. 54(2003) no.6, S.549-568

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Date

13. 7.2008 19:53:22

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Date

7. 2.2005 14:10:22

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Date

22. 7.2006 15:22:28

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Footnote

Vgl. auch: MacRoberts, M.H.: Author motivation for not citing influences

Source

Journal of the American Society for Information Science. 36(1985), S.223-229

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Footnote

Vgl. auch: MacRoberts, M.H.: Author motivation for not citing influences

Source

Journal of the American Society for Information Science. 37(1986), S.34-36

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Abstract

This article examines the impact of the Internet and the age distribution of research scholars on academic citation age with a mathematical model proposed by Barnett, Fink, and Debus (1989) and a revised model that incorporates information about the online environment and scholar age distribution. The modified model fits the data well, accounting for 99.6% of the variance for science citations and 99.8% for social science citations. The Internet's impact on the aging process of academic citations has been very small, accounting for only 0.1% for the social sciences and 0.8% for the sciences. Rather than resulting in the use of more recent citations, the Internet appears to have lengthened the average life of academic citations by 6 to 8 months. The aging of scholars seems to have a greater impact, accounting for 2.8% of the variance for the sciences and 0.9% for the social sciences. However, because the diffusion of the Internet and the aging of the professoriate are correlated over this time period, differentiating their effects is somewhat problematic.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.4, S.526-534

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Abstract

Previous research has demonstrated that lower performance groups have a larger size-dependent cumulative advantage for receiving citations than do top-performance groups. Furthermore, regardless of performance, larger groups have less not-cited publications. Particularly for the lower performance groups, the fraction of not-cited publications decreases considerably with size. These phenomena can be explained with a model in which self-citation acts as a promotion mechanism for external citations. In this article, we show that for self-citations, similar size-dependent scaling rules apply as for citations, but generally the power law exponents are higher for self-citations as compared to citations. We also find that the fraction of self-citations is smaller for the higher performance groups, and this fraction decreases more rapidly with increasing journal impact than that for lower performance groups. An interesting novel finding is that the variance in the correlation of the number of self-citations with size is considerably less than the variance for external citations. This is a clear indication that size is a stronger determinant for self-citations than it is for external citations. Both higher and particularly lower performance groups have a size-dependent cumulative advantage for self-citations, but for the higher performance groups only in the lower impact journals and in fields with low citation density.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.10, S.1631-1643