Search (1150 results, page 1 of 58)

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Abstract

The citation relationships between publications, which are significant for assessing the importance of scholarly components within a network, have been used for various scientific applications. Missing citation metadata in scholarly databases, however, create problems for classical citation-based ranking algorithms and challenge the performance of citation-based retrieval systems. In this research, we utilize a two-step citation analysis method to investigate the importance of publications for which citation information is partially missing. First, we calculate the importance of the author and then use his importance to estimate the publication importance for some selected articles. To evaluate this method, we designed a simulation experiment-"random citation-missing"-to test the two-step citation analysis that we carried out with the Association for Computing Machinery (ACM) Digital Library (DL). In this experiment, we simulated different scenarios in a large-scale scientific digital library, from high-quality citation data, to very poor quality data, The results show that a two-step citation analysis can effectively uncover the importance of publications in different situations. More importantly, we found that the optimized impact from the importance of an author (first step) is exponentially increased when the quality of citation decreases. The findings from this study can further enhance citation-based publication-ranking algorithms for real-world applications.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.7, S.1722-1735

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Abstract

I employed bibliometric and historical methods to study the domain of the Scientific Computing group at Brookhaven National Laboratory (BNL) for an extended period of fifty years, from 1958 to 2007. I noted and confirmed the growing emergence of interdisciplinarity within the group. I also identified a strong, consistent mathematics and physics orientation within it.

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Abstract

Although the analysis of citations in the scholarly literature is now an established and relatively well understood part of information science, not enough is known about citations that can be found on the Web. In particular, are there new Web types, and if so, are these trivial or potentially useful for studying or evaluating research communication? We sought evidence based upon a sample of 1,577 Web citations of the URLs or titles of research articles in 64 open-access journals from biology, physics, chemistry, and computing. Only 25% represented intellectual impact, from references of Web documents (23%) and other informal scholarly sources (2%). Many of the Web/URL citations were created for general or subject-specific navigation (45%) or for self-publicity (22%). Additional analyses revealed significant disciplinary differences in the types of Google unique Web/URL citations as well as some characteristics of scientific open-access publishing on the Web. We conclude that the Web provides access to a new and different type of citation information, one that may therefore enable us to measure different aspects of research, and the research process in particular; but to obtain good information, the different types should be separated.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1631-1644

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Abstract

The mapping of scientific fields, based on principles established in the seventies, has recently shown a remarkable development and applications are now booming with progress in computing efficiency. We examine here the convergence of two thematic mapping approaches, citation-based and word-based, which rely on quite different sociological backgrounds. A corpus in the nanoscience field was broken down into research themes, using the same clustering technique on the 2 networks separately. The tool for comparison is the table of intersections of the M clusters (here M=50) built on either side. A classical visual exploitation of such contingency tables is based on correspondence analysis. We investigate a rearrangement of the intersection table (block modeling), resulting in pseudo-map. The interest of this representation for confronting the two breakdowns is discussed. The amount of convergence found is, in our view, a strong argument in favor of the reliability of bibliometric mapping. However, the outcomes are not convergent at the degree where they can be substituted for each other. Differences highlight the complementarity between approaches based on different networks. In contrast with the strong informetric posture found in recent literature, where lexical and citation markers are considered as miscible tokens, the framework proposed here does not mix the two elements at an early stage, in compliance with their contrasted logic.

Date

8. 1.2011 18:22:50

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.1, S.19-39

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Abstract

The standard data that we use when computing bibliometric rankings of scientists are their publication/ citation records, i.e., so many papers with 0 citation, so many with 1 citation, so many with 2 citations, etc. The standard data for bibliometric rankings of departments have the same structure. It is therefore tempting (and many authors gave in to temptation) to use the same method for computing rankings of scientists and rankings of departments. Depending on the method, this can yield quite surprising and unpleasant results. Indeed, with some methods, it may happen that the "best" department contains the "worst" scientists, and only them. This problem will not occur if the rankings satisfy a property called consistency, recently introduced in the literature. In this article, we explore the consequences of consistency and we characterize two families of consistent rankings.

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.9, S.1761-1769

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Abstract

Recently, Harzing's Publish or Perish software was updated to include Microsoft Academic Search as a second citation database search option for computing various citation-based metrics. This article explores the new search option by scoring 50 top economics and finance journals and comparing them with the results obtained using the original Google Scholar-based search option. The new database delivers significantly smaller scores for all metrics, but the rank correlations across the two databases for the h-index, g-index, AWCR, and e-index are significantly correlated, especially when the time frame is restricted to more recent years. Comparisons are also made to the Article Influence score from eigenfactor.org and to the RePEc h-index, both of which adjust for journal-level self-citations.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.5, S.1079-1084

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Abstract

This article offers a comparative analysis of the personal profiling capabilities of the two most important free citation-based academic search engines, namely, Microsoft Academic Search (MAS) and Google Scholar Citations (GSC). Author profiles can be useful for evaluation purposes once the advantages and the shortcomings of these services are described and taken into consideration. In total, 771 personal profiles appearing in both the MAS and the GSC databases were analyzed. Results show that the GSC profiles include more documents and citations than those in MAS but with a strong bias toward the information and computing sciences, whereas the MAS profiles are disciplinarily better balanced. MAS shows technical problems such as a higher number of duplicated profiles and a lower updating rate than GSC. It is concluded that both services could be used for evaluation proposes only if they are applied along with other citation indices as a way to supplement that information.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.6, S.1149-1156

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Abstract

The last 2 decades have witnessed a dramatic increase in the use of patent citation data in social science research. Facilitated by digitization of the patent data and increasing computing power, a community of practice has grown up that has developed methods for using these data to: measure attributes of innovations such as impact and originality; to trace flows of knowledge across individuals, institutions and regions; and to map innovation networks. The objective of this article is threefold. First, it takes stock of these main uses. Second, it discusses 4 pitfalls associated with patent citation data, related to office, time and technology, examiner, and strategic effects. Third, it highlights gaps in our understanding and offers directions for future research.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.6, S.1360-1374

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Abstract

This paper introduces a keyword map of the labels used by the scientists registered in the Google Scholar Citations (GSC) database from December 2011. In all, 15,000 random queries were formulated to GSC to obtain a list of 26,682 registered users. From this list a network graph of 6,660 labels was built and classified according to the Scopus Subject Area classes. Results display a detailed label map of the most used (>15 times) tags. The structural analysis shows that the core of the network is occupied by computer science-related disciplines that account for the most used and shared labels. This core is surrounded by clusters of disciplines related or close to computing such as Information Sciences, Mathematics, or Bioinformatics. Classical areas such as Chemistry and Physics are marginalized in the graph. It is suggested that GSC would in the future be an accurate source to map Science because it is based on the labels that scientists themselves use to describe their own research activity.

Source

Journal of the American Society for Information Science and Technology. 63(2012) no.12, S.2370-2377

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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

Classifying journals or publications into research areas is an essential element of many bibliometric analyses. Classification usually takes place at the level of journals, where the Web of Science subject categories are the most popular classification system. However, journal-level classification systems have two important limitations: They offer only a limited amount of detail, and they have difficulties with multidisciplinary journals. To avoid these limitations, we introduce a new methodology for constructing classification systems at the level of individual publications. In the proposed methodology, publications are clustered into research areas based on citation relations. The methodology is able to deal with very large numbers of publications. We present an application in which a classification system is produced that includes almost 10 million publications. Based on an extensive analysis of this classification system, we discuss the strengths and the limitations of the proposed methodology. Important strengths are the transparency and relative simplicity of the methodology and its fairly modest computing and memory requirements. The main limitation of the methodology is its exclusive reliance on direct citation relations between publications. The accuracy of the methodology can probably be increased by also taking into account other types of relations-for instance, based on bibliographic coupling.

Source

Journal of the American Society for Information Science and Technology. 63(2012) no.12, S.2378-2392

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Abstract

Recent policy shifts on the part of funding agencies and journal publishers are causing changes in the acknowledgment and citation behaviors of scholars. A growing emphasis on open science and reproducibility is changing how authors cite and acknowledge "research infrastructures"-entities that are used as inputs to or as underlying foundations for scholarly research, including data sets, software packages, computational models, observational platforms, and computing facilities. At the same time, stakeholder interest in quantitative understanding of impact is spurring increased collection and analysis of metrics related to use of research infrastructures. This article reviews work spanning several decades on tracing and assessing the outcomes and impacts from these kinds of research infrastructures. We discuss how research infrastructures are identified and referenced by scholars in the research literature and how those references are being collected and analyzed for the purposes of evaluating impact. Synthesizing common features of a wide range of studies, we identify notable challenges that impede the analysis of impact metrics for research infrastructures and outline key open research questions that can guide future research and applications related to such metrics.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.6, S.1341-1359

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Abstract

In 2014 leading publishers withdrew more than 120 nonsensical publications automatically generated with the SCIgen program. Casual observations suggested that similar problematic papers are still published and sold, without follow-up retractions. No systematic screening has been performed and the prevalence of such nonsensical publications in the scientific literature is unknown. Our contribution is 2-fold. First, we designed a detector that combs the scientific literature for grammar-based computer-generated papers. Applied to SCIgen, it has a 83.6% precision. Second, we performed a scientometric study of the 243 detected SCIgen-papers from 19 publishers. We estimate the prevalence of SCIgen-papers to be 75 per million papers in Information and Computing Sciences. Only 19% of the 243 problematic papers were dealt with: formal retraction (12) or silent removal (34). Publishers still serve and sometimes sell the remaining 197 papers without any caveat. We found evidence of citation manipulation via edited SCIgen bibliographies. This work reveals metric gaming up to the point of absurdity: fraudsters publish nonsensical algorithmically generated papers featuring genuine references. It stresses the need to screen papers for nonsense before peer-review and chase citation manipulation in published papers. Overall, this is yet another illustration of the harmful effects of the pressure to publish or perish.

Source

Journal of the Association for Information Science and Technology. 72(2021) no.12, S.1461-1476

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Abstract

Previous studies have repeatedly demonstrated that the relevance of a citing document is related to the number of times with which the source document is cited. Despite the ease with which electronic documents would permit the incorporation of this information into citation-based document search and retrieval systems, the possibilities of repeated citations remain untapped. Part of this under-utilization may be due to the fact that very little is known regarding the pattern of repeated citations in scholarly literature or how this pattern may vary as a function of journal, academic discipline or self-citation. The current research addresses these unanswered questions in order to facilitate the future incorporation of repeated citation information into document search and retrieval systems. Using data mining of electronic texts, the citation characteristics of nine different journals, covering the three different academic fields (economics, computing, and medicine & biology), were characterized. It was found that the frequency (f) with which a reference is cited N or more times within a document is consistent across the sampled journals and academic fields. Self-citation causes an increase in frequency, and this effect becomes more pronounced for large N. The objectivity, automatability, and insensitivity of repeated citations to journal and discipline, present powerful opportunities for improving citation-based document search.

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Abstract

Interests of researchers who engage with research synthesis methods (RSM) intersect with library and information science (LIS) research and practice. This intersection is described by a summary of conceptualizations of research synthesis in a diverse set of research fields and in the context of Swanson's (1986) discussion of undiscovered public knowledge. Through a selective literature review, research topics that intersect with LIS and RSM are outlined. Topics identified include open access, information retrieval, bias and research information ethics, referencing practices, citation patterns, and data science. Subsequently, bibliometrics and topic modeling are used to present a systematic overview of the visibility of RSM in LIS. This analysis indicates that RSM became visible in LIS in the 1980s. Overall, LIS research has drawn substantially from general and internal medicine, the field's own literature, and business; and is drawn on by health and medical sciences, computing, and business. Through this analytical overview, it is confirmed that research synthesis is more visible in the health and medical literature in LIS; but suggests that, LIS, as a meta-science, has the potential to make substantive contributions to a broader variety of fields in the context of topics related to research synthesis methods.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.8, S.1990-2008

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Abstract

In November 2014, the Nature Index (NI) was introduced (see http://www.natureindex.com) by the Nature Publishing Group (NPG). The NI comprises the primary research articles published in the past 12 months in a selection of reputable journals. Starting from two short comments on the NI (Haunschild & Bornmann, 2015a, 2015b), we undertake an empirical analysis of the NI using comprehensive country data. We investigate whether the huge efforts of computing the NI are justified and whether the size-dependent NI indicators should be complemented by size-independent variants. The analysis uses data from the Max Planck Digital Library in-house database (which is based on Web of Science data) and from the NPG. In the first step of the analysis, we correlate the NI with other metrics that are simpler to generate than the NI. The resulting large correlation coefficients point out that the NI produces similar results as simpler solutions. In the second step of the analysis, relative and size-independent variants of the NI are generated that should be additionally presented by the NPG. The size-dependent NI indicators favor large countries (or institutions) and the top-performing small countries (or institutions) do not come into the picture.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.3, S.653-659

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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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Date

22. 7.2006 18:55:29

Source

Journal of the American Society for Information Science. 41(1990) no.5, S.368-375

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Date

22. 7.2006 18:55:55

Source

Journal of the American Society for Information Science. 41(1990) no.5, S.376-386