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Content

Vgl. unter: https://www.leibniz-science20.de%2Fforschung%2Fprojekte%2Faltmetrics-in-verschiedenen-wissenschaftsdisziplinen%2F&ei=2jTgVaaXGcK4Udj1qdgB&usg=AFQjCNFOPdONj4RKBDf9YDJOLuz3lkGYlg&sig2=5YI3KWIGxBmk5_kv0P_8iQ.

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Abstract

Research on scientific misconduct relies increasingly on retractions of articles. An interdisciplinary line of research has been established that empirically assesses the phenomenon of scientific misconduct using information on retractions, and thus aims to shed light on aspects of misconduct that previously were hidden. However, comparability and interpretability of studies are to a certain extent impeded by an absence of standards in corpus delineation and by the fact that the validity of this empirical data basis has never been systematically scrutinized. This article assesses the conceptual and empirical delineation of retractions against related publication types through a comparative analysis of the coverage and consistency of retraction annotation in the databases PubMed and the Web of Science (WoS), which are both commonly used for empicial studies on retractions. The searching and linking approaches of the WoS were subsequently evaluated. The results indicate that a considerable number of PubMed retracted publications and retractions are not labeled as such in the WoS or are indistinguishable from corrections, which is highly relevant for corpus and sample strategies in the WoS.

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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.

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Abstract

This study uses three bibliometric methods: direct citation, bibliographic coupling, and co-authorship analysis, to investigate interdisciplinary changes in library and information science (LIS) from 1978 to 2007. The results reveal that LIS researchers most frequently cite publications in their own discipline. In addition, half of all co-authors of LIS articles are affiliated with LIS-related institutes. The results confirm that the degree of interdisciplinarity within LIS has increased, particularly co-authorship. However, the study found sources of direct citations in LIS articles are widely distributed across 30 disciplines, but co-authors of LIS articles are distributed across only 25 disciplines. The degree of interdisciplinarity was found ranging from 0.61 to 0.82 with citation to references in all articles being the highest and that of co-authorship being the lowest. Percentages of contribution attributable to LIS show a decreasing tendency based on the results of direct citation and co-authorship analysis, but an increasing tendency based on those of bibliographic coupling analysis. Such differences indicate each of the three bibliometric methods has its strength and provides insights respectively for viewing various aspects of interdisciplinarity, suggesting the use of no single bibliometric method can reveal all aspects of interdisciplinarity due to its multifaceted nature.

Source

Journal of the American Society for Information Science and Technology. 63(2012) no.1, S.22-33

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Abstract

One of the solutions to help scientists filter the most relevant publications and, thus, to stay current on developments in their fields during the transition from "little science" to "big science", was the introduction of citation indexing as a Wellsian "World Brain" (Garfield, 1964) of scientific information: It is too much to expect a research worker to spend an inordinate amount of time searching for the bibliographic descendants of antecedent papers. It would not be excessive to demand that the thorough scholar check all papers that have cited or criticized such papers, if they could be located quickly. The citation index makes this check practicable (Garfield, 1955, p. 108). In retrospective, citation indexing can be perceived as a pre-social web version of crowdsourcing, as it is based on the concept that the community of citing authors outperforms indexers in highlighting cognitive links between papers, particularly on the level of specific ideas and concepts (Garfield, 1983). Over the last 50 years, citation analysis and more generally, bibliometric methods, have developed from information retrieval tools to research evaluation metrics, where they are presumed to make scientific funding more efficient and effective (Moed, 2006). However, the dominance of bibliometric indicators in research evaluation has also led to significant goal displacement (Merton, 1957) and the oversimplification of notions of "research productivity" and "scientific quality", creating adverse effects such as salami publishing, honorary authorships, citation cartels, and misuse of indicators (Binswanger, 2015; Cronin and Sugimoto, 2014; Frey and Osterloh, 2006; Haustein and Larivière, 2015; Weingart, 2005).

Date

20. 1.2015 18:30:22

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Abstract

This brief communication analyzes the statistics and methods Lotka used to derive his inverse square law of scientific productivity from the standpoint of modern theory. It finds that he violated the norms of this theory by extremely truncating his data on the right. It also proves that Lotka himself played an important role in establishing the commonly used method of identifying power-law behavior by the R2 fit to a regression line on a log-log plot that modern theory considers unreliable by basing the derivation of his law on this very method.

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Abstract

The domain of knowledge organization (KO) represents a foundational area of information science. One way to better understand the intellectual structure of the KO domain is to apply bibliometric methods to key contributors to the literature. This study analyzes the most prolific contributing authors to the journal Knowledge Organization, the sources they cite and the citations they receive for the period 1993 to 2016. The analyses were conducted using visualization outcomes of citation, co-citation and author bibliographic coupling analysis to reveal theoretical points of reference among authors and the most prominent research themes that constitute this scientific community. Birger Hjørland was the most cited author, and was situated at or near the middle of each of the maps based on different citation relationships. The proximities between authors resulting from the different citation relationships demonstrate how authors situate themselves intellectually through the citations they give and how other authors situate them through the citations received. There is a consistent core of theoretical references as well among the most productive authors. We observed a close network of scholarly communication between the authors cited in this core, which indicates the actual role of the journal Knowledge Organization as a space for knowledge construction in the area of knowledge organization.

Source

Knowledge organization. 45(2018) no.1, S.13-22

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Abstract

In the past several years studies have started to appear comparing the accuracies of various science mapping approaches. These studies primarily compare the cluster solutions resulting from different similarity approaches, and give varying results. In this study we compare the accuracies of cluster solutions of a large corpus of 2,153,769 recent articles from the biomedical literature (2004-2008) using four similarity approaches: co-citation analysis, bibliographic coupling, direct citation, and a bibliographic coupling-based citation-text hybrid approach. Each of the four approaches can be considered a way to represent the research front in biomedicine, and each is able to successfully cluster over 92% of the corpus. Accuracies are compared using two metrics-within-cluster textual coherence as defined by the Jensen-Shannon divergence, and a concentration measure based on the grant-to-article linkages indexed in MEDLINE. Of the three pure citation-based approaches, bibliographic coupling slightly outperforms co-citation analysis using both accuracy measures; direct citation is the least accurate mapping approach by far. The hybrid approach improves upon the bibliographic coupling results in all respects. We consider the results of this study to be robust given the very large size of the corpus, and the specificity of the accuracy measures used.

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Abstract

This study explores the similarity among six types of scholarly networks aggregated at the institution level, including bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks. Cosine distance is chosen to measure the similarities among the six networks. The authors found that topical networks and coauthorship networks have the lowest similarity; cocitation networks and citation networks have high similarity; bibliographic coupling networks and cocitation networks have high similarity; and coword networks and topical networks have high similarity. In addition, through multidimensional scaling, two dimensions can be identified among the six networks: Dimension 1 can be interpreted as citation-based versus noncitation-based, and Dimension 2 can be interpreted as social versus cognitive. The authors recommend the use of hybrid or heterogeneous networks to study research interaction and scholarly communications.

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Abstract

Journals in the Information Science & Library Science category of Journal Citation Reports (JCR) were compared using both bibliometric and bibliographic features. Data collected covered journal impact factor (JIF), number of issues per year, number of authors per article, longevity, editorial board membership, frequency of publication, number of databases indexing the journal, number of aggregators providing full-text access, country of publication, JCR categories, Dewey decimal classification, and journal statement of scope. Three features significantly correlated with JIF: number of editorial board members and number of JCR categories in which a journal is listed correlated positively; journal longevity correlated negatively with JIF. Coword analysis of journal descriptions provided a proximity clustering of journals, which differed considerably from the clusters based on editorial board membership. Finally, a multiple linear regression model was built to predict the JIF based on all the collected bibliographic features.

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Abstract

Historically, co-citation models have been based only on bibliographic information. Full-text analysis offers the opportunity to significantly improve the quality of the signals upon which these co-citation models are based. In this work we study the effect of reference proximity on the accuracy of co-citation clusters. Using a corpus of 270,521 full text documents from 2007, we compare the results of traditional co-citation clustering using only the bibliographic information to results from co-citation clustering where proximity between reference pairs is factored into the pairwise relationships. We find that accounting for reference proximity from full text can increase the textual coherence (a measure of accuracy) of a co-citation cluster solution by up to 30% over the traditional approach based on bibliographic information.

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Abstract

This study explored the feasibility of using Web hyperlink data to study European political Web sites. Ninety-six European Union (EU) political parties belonging to a wide range of ideological, historical, and linguistic backgrounds were included in the study. Various types of data on Web links to party Web sites were collected. The Web colink data were visualized using multidimensional scaling (MDS), while the inlink data were analyzed with a 2-way analysis of variance test. The results showed that Web hyperlink data did reflect some political patterns in the EU. The MDS maps showed clusters of political parties along ideological, historical, linguistic, and social lines. Statistical analysis based on inlink counts further confirmed that there was a significant difference along the line of the political history of a country, such that left-wing parties in the former communist countries received considerably fewer inlinks to their Web sites than left-wing parties in countries without a history of communism did. The study demonstrated the possibility of using Web hyperlink data to gain insights into political situations in the EU. This suggests the richness of Web hyperlink data and its potential in studying social-political phenomena.

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Abstract

In 1965, Price foresaw the day when a citation-based taxonomy of science and technology would be delineated and correspondingly used for science policy. A taxonomy needs to be comprehensive and accurate if it is to be useful for policy making, especially now that policy makers are utilizing citation-based indicators to evaluate people, institutions and laboratories. Determining the accuracy of a taxonomy, however, remains a challenge. Previous work on the accuracy of partition solutions is sparse, and the results of those studies, although useful, have not been definitive. In this study we compare the accuracies of topic-level taxonomies based on the clustering of documents using direct citation, bibliographic coupling, and co-citation. Using a set of new gold standards-articles with at least 100 references-we find that direct citation is better at concentrating references than either bibliographic coupling or co-citation. Using the assumption that higher concentrations of references denote more accurate clusters, direct citation thus provides a more accurate representation of the taxonomy of scientific and technical knowledge than either bibliographic coupling or co-citation. We also find that discipline-level taxonomies based on journal schema are highly inaccurate compared to topic-level taxonomies, and recommend against their use.

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Abstract

This paper analyzes the bibliographic references made by all papers published by ACM in 2006. Both an automatic classification of all references and a human classification of a random sample of them resulted that around 40% of the references are to conference proceedings papers, around 30% are to journal papers, and around 8% are to books. Among the other types of documents, standards and RFC correspond to 3% of the references, technical and other reports correspond to 4%, and other Web references to 3%. Among the documents cited at least 10 times by the 2006 ACM papers, 41% are conferences papers, 37% are books, and 16% are journal papers.

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Abstract

This study analyzes coauthorship patterns in the social sciences and humanities (SSH) for the period 2000 to 2010. The basis for the analysis is the Flemish Academic Bibliographic Database for the Social Sciences and Humanities (VABB-SHW), a comprehensive bibliographic database of peer-reviewed publications in the SSH by researchers affiliated with Flemish universities. Combining data on journal articles and book chapters, our findings indicate that collaborative publishing in the SSH is increasing, though considerable differences between disciplines remain. Conversely, we did observe a sharp decline in single-author publishing. We further demonstrate that coauthored SSH articles in journals indexed in the Web of Science (WoS) generally have a higher (and growing) number of coauthors than do either those in non-WoS journals or book chapters. This illustrates the need to include non-WoS data and book chapters when studying coauthorship in the SSH.

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Abstract

This article describes the results of our analysis of the data from the CiteSeer digital library. First, we examined the data from the point of view of source top-level Internet domains from which the data were collected. Second, we measured country shares in publications indexed by CiteSeer and compared them to those based on mainstream bibliographic data from the Web of Science and Scopus. And third, we concentrated on analyzing publications and their citations aggregated by countries. This way, we generated rankings of the most influential countries in computer science using several non-recursive as well as recursive methods such as citation counts or PageRank. We conclude that even if East Asian countries are underrepresented in CiteSeer, its data may well be used along with other conventional bibliographic databases for comparing the computer science research productivity and performance of countries.

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Abstract

This study continues a long history of author cocitation analysis (and more recently, author bibliographic coupling analysis) of the intellectual structure of information science (IS) into the time period 2006 to 2010 (IS 2006-2010). We find that web technologies continue to drive developments, especially at the research front, although perhaps more indirectly than before. A broadening of perspectives is visible in IS 2006-2010, where network science becomes influential and where full-text analysis methods complement traditional computer science influences. Research in the areas of the h-index and mapping of science appears to have been highlights of IS 2006-2011. This study tests and confirms a forecast made previously by comparing knowledge-base and research-front findings for IS 2001-2005, which expected both the information retrieval (IR) systems and webometrics specialties to shrink in 2006 to 2010. A corresponding comparison of the knowledge base and research front of IS 2006-2010 suggests a continuing decline of the IR systems specialty in the near future, but also a considerable (re)growth of the webometrics area after a period of decline from 2001 to 2005 and 2006 to 2010, with the latter due perhaps in part to its contribution to an emerging web science.

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Abstract

Knowledge Organization (KO) theoretical foundations are still being developed in a continuous process of epistemological, theoretical and methodological consolidation. The remarkable growth of scientific records has stimulated the analysis of this production and the creation of instruments to evaluate the behavior of science became indispensable. We propose the Domain Analysis of KO in North America through the citation analysis of North American Symposium on Knowledge Organization (NASKO) proceedings (2007 - 2015). We present the citation, co-citation and bibliographic coupling analysis to visualize and recognize the researchers that influence the scholarly communication in this domain. The most prolific authors through NASKO conferences are Smiraglia, Tennis, Green, Dousa, Grant Campbell, Pimentel, Beak, La Barre, Kipp and Fox. Regarding their theoretical references, Hjørland, Olson, Smiraglia, and Ranganathan are the authors who most inspired the event's studies. The co-citation network shows the highest frequency is between Olson and Mai, followed by Hjørland and Mai and Beghtol and Mai, consolidating Mai and Hjørland as the central authors of the theoretical references in NASKO. The strongest theoretical proximity in author bibliographic coupling network occurs between Fox and Tennis, Dousa and Tennis, Tennis and Smiraglia, Dousa and Beak, and Pimentel and Tennis, highlighting Tennis as central author, that interconnects the others in relation to KO theoretical references in NASKO. The North American chapter has demonstrated a strong scientific production as well as a high level of concern with theoretical and epistemological questions, gathering researchers from different countries, universities and knowledge areas.

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Abstract

Characteristics of the Journal of the American Society for Information Science and Technology and 76 other journals listed in the InformationSystems category of the Journal Citation Reports-Science edition 2009 were analyzed. Besides reporting usual bibliographic indicators, we investigated the human cornerstone of any peer-reviewed journal: its editorial board. Demographic data about the 2,846 gatekeepers serving in information systems (IS) editorial boards were collected. We discuss various scientometric indicators supported by descriptive statistics. Our findings reflect the great variety of IS journals in terms of research output, author communities, editorial boards, and gatekeeper demographics (e.g., diversity in gender and location), seniority, authority, and degree of involvement in editorial boards. We believe that these results may help the general public and scholars (e.g., readers, authors, journal gatekeepers, policy makers) to revise and increase their knowledge of scholarly communication in the IS field. The EB_IS_2009 dataset supporting this scientometric study is released as online supplementary material to this article to foster further research on editorial boards.

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