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34
Mapping the backbone of science
- SCIENTOMETRICS
, 2005
"... This paper presents a new map representing the structure of all of science, based on journal articles, including both the natural and social sciences. Similar to cartographic maps of our world, the map of science provides a bird’s eye view of today’s scientific landscape. It can be used to visually ..."
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Cited by 99 (4 self)
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This paper presents a new map representing the structure of all of science, based on journal articles, including both the natural and social sciences. Similar to cartographic maps of our world, the map of science provides a bird’s eye view of today’s scientific landscape. It can be used to visually identify major areas of science, their size, similarity, and interconnectedness. In order to be useful, the map needs to be accurate on a local and on a global scale. While our recent work has focused on the former aspect, 1 this paper summarizes results on how to achieve structural accuracy. Eight alternative measures of journal similarity were applied to a data set of 7,121 journals covering over 1 million documents in the combined Science Citation and Social Science Citation Indexes. For each journal similarity measure we generated two-dimensional spatial layouts using the force-directed graph layout tool, VxOrd. Next, mutual information values were calculated for each graph at different clustering levels to give a measure of structural accuracy for each map. The best co-citation and inter-citation maps according to local and structural accuracy were selected and are presented and characterized. These two maps are compared to establish robustness. The inter-citation map is then used to examine linkages between disciplines. Biochemistry appears as the most interdisciplinary discipline in science.
A Global Map of Science Based on the ISI Subject Categories
, 2007
"... The ISI subject categories classify journals included in the Science Citation Index (SCI). The aggregated journal-journal citation matrix contained in the Journal Citation Reports can be aggregated on the basis of these categories. This leads to an asymmetrical transaction matrix (citing versus cite ..."
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Cited by 45 (11 self)
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The ISI subject categories classify journals included in the Science Citation Index (SCI). The aggregated journal-journal citation matrix contained in the Journal Citation Reports can be aggregated on the basis of these categories. This leads to an asymmetrical transaction matrix (citing versus cited) which is much more densely populated than the underlying matrix at the journal level. Exploratory factor analysis leads us to opt for a fourteen-factor solution. This solution can easily be interpreted as the disciplinary structure of science. The nested maps of science (corresponding to 14 factors, 172 categories, and 6,164 journals) are brought online at
Betweenness Centrality” as an Indicator of the “Interdisciplinarity” of Scientific Journals
- Journal of the American Society for Information Science and Technology
, 2006
"... In addition to science citation indicators of journals like impact and immediacy, social network analysis provides a set of centrality measures like degree, betweenness, and closeness centrality. These measures are first analyzed for the entire set of 7,379 journals included in the Journal Citation ..."
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Cited by 45 (10 self)
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In addition to science citation indicators of journals like impact and immediacy, social network analysis provides a set of centrality measures like degree, betweenness, and closeness centrality. These measures are first analyzed for the entire set of 7,379 journals included in the Journal Citation Reports of the Science Citation Index and the Social Sciences Citation Index 2004, and then also in relation to local citation environments which can be considered as proxies of specialties and disciplines. Betweenness centrality is shown to be an indicator of the interdisciplinarity of journals, but only in local citation environments and after normalization because otherwise the influence of degree centrality (size) overshadows the betweenness-centrality measure. The indicator is applied to a variety of citation environments, including policy-relevant ones like biotechnology and nanotechnology. The values of the indicator remain sensitive to the delineations of the set because of the indicator’s local character. Maps showing 1 interdisciplinarity of journals in terms of betweenness centrality can be drawn using information about journal citation environments which is available online.
Content-based and Algorithmic Classifications of Journals: Perspectives on the
- Dynamics of Scientific Communication and Indexer Effects Journal of the American Society for Information Science and Technology, In print; DOI: 10.1002/asi.21086
, 2009
"... The aggregated journal-journal citation matrix—based on the Journal Citation Reports (JCR) of the Science Citation Index—can be decomposed by indexers and/or algorithmically. In this study, we test the results of two recently available algorithms for the decomposition of large matrices against two c ..."
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Cited by 38 (23 self)
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The aggregated journal-journal citation matrix—based on the Journal Citation Reports (JCR) of the Science Citation Index—can be decomposed by indexers and/or algorithmically. In this study, we test the results of two recently available algorithms for the decomposition of large matrices against two content-based classifications of journals: the ISI Subject Categories and the field/subfield classification of Glänzel & Schubert (2003). The content-based schemes allow for the attribution of more than a single category to a journal, whereas the algorithms maximize the ratio of within-category citations over between-category citations in the aggregated category-category citation matrix. By adding categories, indexers generate between-category citations, which may enrich the database, for example, in the case of inter-disciplinary developments. The consequent indexer effects are significant in sparse areas of the matrix more than in denser ones. Algorithmic decompositions, on the other hand, are more heavily skewed towards a relatively small number of categories, while this is deliberately counter-acted upon in the case of content-based classifications. Because of the indexer effects, science policy studies and the sociology of science should be careful when using content-based classifications, which are made for bibliographic disclosure, and not for the purpose of analyzing latent structures in scientific communications. Despite the large differences among them, the four classification schemes enable us to generate surprisingly similar maps of science at the global level. Erroneous classifications are cancelled as noise at the aggregate level, but may disturb the evaluation locally.
Identifying a better measure of relatedness for mapping science
- Journal of the American Society for Information Science and Technology
, 2006
"... Measuring the relatedness between bibliometric units (journals, documents, authors, or words) is a central task in bibliometric analysis. Relatedness measures are used for many different tasks, among them the generating of maps, or visual pictures, showing the relationship between all items from the ..."
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Cited by 36 (5 self)
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Measuring the relatedness between bibliometric units (journals, documents, authors, or words) is a central task in bibliometric analysis. Relatedness measures are used for many different tasks, among them the generating of maps, or visual pictures, showing the relationship between all items from these data. Despite the importance of these tasks, there has been little written on how to quantitatively evaluate the accuracy of relatedness measures or the resulting maps. The authors propose a new framework for assessing the performance of relatedness measures and visualization algorithms that contains four factors: accuracy, coverage, scalability, and robustness. This method was applied to 10 measures of journal–journal relatedness to determine the best measure. The 10 relatedness measures were then used as inputs to a visualization algorithm to create an additional 10 measures of journal–journal relatedness based on the distances between pairs of journals in two-dimensional space. This second step determines robustness (i.e., which measure remains best after dimension reduction). Results show that, for low coverage (under 50%), the Pearson correlation is the most accurate raw relatedness measure. However, the best overall measure, both at high coverage, and after dimension reduction, is the cosine index or a modified cosine index. Results also showed that the visualization algorithm increased local accuracy for most measures. Possible reasons for this counterintuitive finding are discussed.
How to normalize cooccurrence data? An analysis of some wellknown similarity measures
- Journal of the American Society for Information Science and Technology
, 2009
"... Bibliographic data and classifications of all the ERIM reports are also available on the ERIM website: www.erim.eur.nl ..."
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Cited by 20 (4 self)
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Bibliographic data and classifications of all the ERIM reports are also available on the ERIM website: www.erim.eur.nl
Measuring researcher interdisciplinarity
- Scientometrics
, 2007
"... We offer two metrics that together help gauge how interdisciplinary a body of research is. Both draw upon Web of Knowledge Subject Categories (SCs) as key units of analysis. We have assembled two substantial Web of Knowledge samples from which to determine how closely individual SCs relate to each o ..."
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Cited by 17 (3 self)
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We offer two metrics that together help gauge how interdisciplinary a body of research is. Both draw upon Web of Knowledge Subject Categories (SCs) as key units of analysis. We have assembled two substantial Web of Knowledge samples from which to determine how closely individual SCs relate to each other. “Integration ” measures the extent to which a research article cites diverse SCs. “Specialization ” considers the spread of SCs in which the body of research (e.g., the work of a given author in a specified time period) is published. Pilot results for a sample of researchers show a surprising degree of interdisciplinarity. Background Research spirals inward; science cascades outward. This dual image supports a vital realization – scientific advance requires knowledge transfer among researchers who
Mendeley readership altmetrics for the social sciences and humanities: Research evaluation and knowledge flows 1
"... Although there is evidence that counting the readers of an article in the social reference site, Mendeley, may help to capture its research impact, the extent to which this is true for different scientific fields is unknown. This study compares Mendeley readership counts with citations for different ..."
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Cited by 12 (8 self)
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Although there is evidence that counting the readers of an article in the social reference site, Mendeley, may help to capture its research impact, the extent to which this is true for different scientific fields is unknown. This study compares Mendeley readership counts with citations for different social sciences and humanities disciplines. The overall correlation between Mendeley readership counts and citations for the social sciences was higher than for the humanities. Low and medium correlations between Mendeley bookmarks and citation counts in all the investigated disciplines suggest that these measures reflect different aspects of research impact. Mendeley data was also used to discover patterns of information flow between scientific fields. Comparing information flows based on Mendeley bookmarking data and cross disciplinary citation analysis for the disciplines revealed substantial similarities and some differences. Thus, the evidence from this study suggests that Mendeley readership data could be used to help capture knowledge transfer across scientific disciplines, especially for people that read but do not author articles, as well as giving impact evidence at an earlier stage than is possible with citation counts.
return The Delineation of an Interdisciplinary Specialty in terms of a Journal Set: The Case of Communication Studies Journal of the American Society for Information Science & Technology (forthcoming)
"... A journal set in an interdisciplinary or newly developing area can be determined by including the journals classified under the most relevant ISI Subject Categories into a journal-journal citation matrix. Despite the fuzzy character of borders, factor analysis of the citation patterns enables us to ..."
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Cited by 10 (5 self)
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A journal set in an interdisciplinary or newly developing area can be determined by including the journals classified under the most relevant ISI Subject Categories into a journal-journal citation matrix. Despite the fuzzy character of borders, factor analysis of the citation patterns enables us to delineate the specific set by discarding the noise. This methodology is illustrated using communication studies as a hybrid development between political science and social psychology. The development can be visualized using animations which support the claim that a specific journal set in communication studies is increasingly developing, notably in the “being cited ” patterns. The resulting set of 28 journals in communication studies is smaller and more focused than the 45 journals classified by the ISI Subject Categories as “Communication. ” The proposed method is tested for its robustness by extending the relevant environments to sets including many more journals.
