Search (1187 results, page 1 of 60)

  • × theme_ss:"Informetrie"
  1. Shibata, N.; Kajikawa, Y.; Takeda, Y.; Matsushima, K.: Comparative study on methods of detecting research fronts using different types of citation (2009) 0.17
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    Abstract
    In this article, we performed a comparative study to investigate the performance of methods for detecting emerging research fronts. Three types of citation network, co-citation, bibliographic coupling, and direct citation, were tested in three research domains, gallium nitride (GaN), complex network (CNW), and carbon nanotube (CNT). Three types of citation network were constructed for each research domain, and the papers in those domains were divided into clusters to detect the research front. We evaluated the performance of each type of citation network in detecting a research front by using the following measures of papers in the cluster: visibility, measured by normalized cluster size, speed, measured by average publication year, and topological relevance, measured by density. Direct citation, which could detect large and young emerging clusters earlier, shows the best performance in detecting a research front, and co-citation shows the worst. Additionally, in direct citation networks, the clustering coefficient was the largest, which suggests that the content similarity of papers connected by direct citations is the greatest and that direct citation networks have the least risk of missing emerging research domains because core papers are included in the largest component.
    Date
    22. 3.2009 17:52:50
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.571-580
  2. Ridenour, L.: Boundary objects : measuring gaps and overlap between research areas (2016) 0.16
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    Abstract
    The aim of this paper is to develop methodology to determine conceptual overlap between research areas. It investigates patterns of terminology usage in scientific abstracts as boundary objects between research specialties. Research specialties were determined by high-level classifications assigned by Thomson Reuters in their Essential Science Indicators file, which provided a strictly hierarchical classification of journals into 22 categories. Results from the query "network theory" were downloaded from the Web of Science. From this file, two top-level groups, economics and social sciences, were selected and topically analyzed to provide a baseline of similarity on which to run an informetric analysis. The Places & Spaces Map of Science (Klavans and Boyack 2007) was used to determine the proximity of disciplines to one another in order to select the two disciplines use in the analysis. Groups analyzed share common theories and goals; however, groups used different language to describe their research. It was found that 61% of term words were shared between the two groups.
  3. Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006) 0.16
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    Abstract
    This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.
    Date
    22. 7.2006 16:11:05
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.3, S.359-377
  4. Stvilia, B.; Hinnant, C.C.; Schindler, K.; Worrall, A.; Burnett, G.; Burnett, K.; Kazmer, M.M.; Marty, P.F.: Composition of scientific teams and publication productivity at a national science lab (2011) 0.14
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    Abstract
    The production of scientific knowledge has evolved from a process of inquiry largely based on the activities of individual scientists to one grounded in the collaborative efforts of specialized research teams. This shift brings to light a new question: how the composition of scientific teams affects their production of knowledge. This study employs data from 1,415 experiments conducted at the National High Magnetic Field Laboratory (NHMFL) between 2005 and 2008 to identify and select a sample of 89 teams and examine whether team diversity and network characteristics affect productivity. The study examines how the diversity of science teams along several variables affects overall team productivity. Results indicate several diversity measures associated with network position and team productivity. Teams with mixed institutional associations were more central to the overall network compared with teams that primarily comprised NHMFL's own scientists. Team cohesion was positively related to productivity. The study indicates that high productivity in teams is associated with high disciplinary diversity and low seniority diversity of team membership. Finally, an increase in the share of senior members negatively affects productivity, and teams with members in central structural positions perform better than other teams.
    Date
    22. 1.2011 13:19:42
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.270-283
  5. Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.14
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    Abstract
    In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.
    Date
    22. 3.2009 17:49:11
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.557-570
  6. Milard, B.; Pitarch, Y.: Egocentric cocitation networks and scientific papers destinies (2023) 0.14
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    Abstract
    To what extent is the destiny of a scientific paper shaped by the cocitation network in which it is involved? What are the social contexts that can explain these structuring? Using bibliometric data, interviews with researchers, and social network analysis, this article proposes a typology based on egocentric cocitation networks that displays a quadruple structuring (before and after publication): polarization, clusterization, atomization, and attrition. It shows that the academic capital of the authors and the intellectual resources of their research are key factors of these destinies, as are the social relations between the authors concerned. The circumstances of the publishing are also correlated with the structuring of the egocentric cocitation networks, showing how socially embedded they are. Finally, the article discusses the contribution of these original networks to the analyze of scientific production and its dynamics.
    Date
    21. 3.2023 19:22:14
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.4, S.415-433
  7. Noyons, E.C.M.; Raan, A.F.J. van: Monitoring scientific developments from a dynamic perspective : self-organized structuring to map neural network research (1998) 0.14
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    Abstract
    With the help of bibliometric mapping techniques, we have developed a methodology of 'self-organized' structuring of scientific fields. This methodology is applied to the field of neural network research
    Source
    Journal of the American Society for Information Science. 49(1998) no.1, S.68-81
  8. Tonta, Y.: Scholarly communication and the use of networked information sources (1996) 0.13
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    Abstract
    Examines the use of networked information sources in scholarly communication. Networked information sources are defined broadly to cover: documents and images stored on electronic network hosts; data files; newsgroups; listservs; online information services and electronic periodicals. Reports results of a survey to determine how heavily, if at all, networked information sources are cited in scholarly printed periodicals published in 1993 and 1994. 27 printed periodicals, representing a wide range of subjects and the most influential periodicals in their fields, were identified through the Science Citation Index and Social Science Citation Index Journal Citation Reports. 97 articles were selected for further review and references, footnotes and bibliographies were checked for references to networked information sources. Only 2 articles were found to contain such references. Concludes that, although networked information sources facilitate scholars' work to a great extent during the research process, scholars have yet to incorporate such sources in the bibliographies of their published articles
    Source
    IFLA journal. 22(1996) no.3, S.240-245
  9. Xu, C.; Ma, B.; Chen, X.; Ma, F.: Social tagging in the scholarly world (2013) 0.11
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    Abstract
    The number of research studies on social tagging has increased rapidly in the past years, but few of them highlight the characteristics and research trends in social tagging. A set of 862 academic documents relating to social tagging and published from 2005 to 2011 was thus examined using bibliometric analysis as well as the social network analysis technique. The results show that social tagging, as a research area, develops rapidly and attracts an increasing number of new entrants. There are no key authors, publication sources, or research groups that dominate the research domain of social tagging. Research on social tagging appears to focus mainly on the following three aspects: (a) components and functions of social tagging (e.g., tags, tagging objects, and tagging network), (b) taggers' behaviors and interface design, and (c) tags' organization and usage in social tagging. The trend suggest that more researchers turn to the latter two integrated with human computer interface and information retrieval, although the first aspect is the fundamental one in social tagging. Also, more studies relating to social tagging pay attention to multimedia tagging objects and not only text tagging. Previous research on social tagging was limited to a few subject domains such as information science and computer science. As an interdisciplinary research area, social tagging is anticipated to attract more researchers from different disciplines. More practical applications, especially in high-tech companies, is an encouraging research trend in social tagging.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.10, S.2045-2057
  10. Liao, C.H.: Exploring the social effect of outstanding scholars on future research accomplishments (2017) 0.10
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    Abstract
    Outstanding scholars have generally been regarded as having special influence that enables them to publish articles in top-tier journals and obtain higher levels of research funding. This study proposes that the social effect of an outstanding scholar, which is derived from the halo effect and the Matthew effect, is favorable for the expansion of the scholar's personal research network and will improve that scholar's future research accomplishments. Data for a total of 101 outstanding information systems scholars and 36 ordinary scholars were collected. The definition of an outstanding scholar is based on the quality and quantity of their publications. The results show that the social effect of the outstanding scholars is beneficial for the development of a research network, including 3 types of network structures. In addition, being highly connected with colleagues leads to higher research accomplishments in terms of quantity, while being connected with colleagues from different sub-fields leads to higher research accomplishments in terms of novelty. Additionally, this study found that the social effect of outstanding scholars is a double-edged sword, with both positive and negative impacts on research accomplishments. The findings contribute several theoretical and practical implications for future research.
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.10, S.2449-2459
  11. Castanha, R.C.G.; Wolfram, D.: ¬The domain of knowledge organization : a bibliometric analysis of prolific authors and their intellectual space (2018) 0.10
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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
  12. Leydesdorff, L.; Shin, J.C.: How to evaluate universities in terms of their relative citation impacts : fractional counting of citations and the normalization of differences among disciplines (2011) 0.10
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    Abstract
    Fractional counting of citations can improve on ranking of multidisciplinary research units (such as universities) by normalizing the differences among fields of science in terms of differences in citation behavior. Furthermore, normalization in terms of citing papers abolishes the unsolved questions in scientometrics about the delineation of fields of science in terms of journals and normalization when comparing among different (sets of) journals. Using publication and citation data of seven Korean research universities, we demonstrate the advantages and the differences in the rankings, explain the possible statistics, and suggest ways to visualize the differences in (citing) audiences in terms of a network.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.6, S.1146-1155
  13. Zhao, D.; Strotmann, A.: ¬The knowledge base and research front of information science 2006-2010 : an author cocitation and bibliographic coupling analysis (2014) 0.10
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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.
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.5, S.995-1006
  14. Zhao, R.; Wei, M.; Quan, W.: Evolution of think tanks studies in view of a scientometrics perspective (2017) 0.10
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    Abstract
    The paper presents a scientometrics analysis of research work done on the emerging area of think tanks, which are regarded as a domain of information science. Research on think tanks started during the last century and in recent years has gained tremendous momentum. It is considered one of the most important emerging domains of research in information science. We have analyzed the research output data on think tanks during 2006-2016 indexed in the Web of KnowledgeT and Scopus®. Our study objectively explores the document co-citation clusters of 1,450 bibliographic records to identify the origin of think tanks and hot research specialties of the domain. CiteSpace was used to visualize the perspective of the think tanks domain. Pivotal articles, prominent authors, active disciplines and institutions have been identified by network analysis. This article describes the latest development of a generic approach to detect and visualize emerging trends and transient patterns in think tanks.
  15. Liu, D.-R.; Shih, M.-J.: Hybrid-patent classification based on patent-network analysis (2011) 0.09
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    Abstract
    Effective patent management is essential for organizations to maintain their competitive advantage. The classification of patents is a critical part of patent management and industrial analysis. This study proposes a hybrid-patent-classification approach that combines a novel patent-network-based classification method with three conventional classification methods to analyze query patents and predict their classes. The novel patent network contains various types of nodes that represent different features extracted from patent documents. The nodes are connected based on the relationship metrics derived from the patent metadata. The proposed classification method predicts a query patent's class by analyzing all reachable nodes in the patent network and calculating their relevance to the query patent. It then classifies the query patent with a modified k-nearest neighbor classifier. To further improve the approach, we combine it with content-based, citation-based, and metadata-based classification methods to develop a hybrid-classification approach. We evaluate the performance of the hybrid approach on a test dataset of patent documents obtained from the U.S. Patent and Trademark Office, and compare its performance with that of the three conventional methods. The results demonstrate that the proposed patent-network-based approach yields more accurate class predictions than the patent network-based approach.
    Date
    22. 1.2011 13:04:21
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.246-256
  16. Radev, D.R.; Joseph, M.T.; Gibson, B.; Muthukrishnan, P.: ¬A bibliometric and network analysis of the field of computational linguistics (2016) 0.09
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    Abstract
    The ACL Anthology is a large collection of research papers in computational linguistics. Citation data were obtained using text extraction from a collection of PDF files with significant manual postprocessing performed to clean up the results. Manual annotation of the references was then performed to complete the citation network. We analyzed the networks of paper citations, author citations, and author collaborations in an attempt to identify the most central papers and authors. The analysis includes general network statistics, PageRank, metrics across publication years and venues, the impact factor and h-index, as well as other measures.
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.3, S.683-706
  17. Thelwall, M.; Sud, P.; Wilkinson, D.: Link and co-inlink network diagrams with URL citations or title mentions (2012) 0.09
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    Abstract
    Webometric network analyses have been used to map the connectivity of groups of websites to identify clusters, important sites or overall structure. Such analyses have mainly been based upon hyperlink counts, the number of hyperlinks between a pair of websites, although some have used title mentions or URL citations instead. The ability to automatically gather hyperlink counts from Yahoo! ceased in April 2011 and the ability to manually gather such counts was due to cease by early 2012, creating a need for alternatives. This article assesses URL citations and title mentions as possible replacements for hyperlinks in both binary and weighted direct link and co-inlink network diagrams. It also assesses three different types of data for the network connections: hit count estimates, counts of matching URLs, and filtered counts of matching URLs. Results from analyses of U.S. library and information science departments and U.K. universities give evidence that metrics based upon URLs or titles can be appropriate replacements for metrics based upon hyperlinks for both binary and weighted networks, although filtered counts of matching URLs are necessary to give the best results for co-title mention and co-URL citation network diagrams.
    Date
    6. 4.2012 18:16:22
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.4, S.805-816
  18. Aris, A.; Shneiderman, B.; Qazvinian, V.; Radev, D.: Visual overviews for discovering key papers and influences across research fronts (2009) 0.09
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    Abstract
    Gaining a rapid overview of an emerging scientific topic, sometimes called research fronts, is an increasingly common task due to the growing amount of interdisciplinary collaboration. Visual overviews that show temporal patterns of paper publication and citation links among papers can help researchers and analysts to see the rate of growth of topics, identify key papers, and understand influences across subdisciplines. This article applies a novel network-visualization tool based on meaningful layouts of nodes to present research fronts and show citation links that indicate influences across research fronts. To demonstrate the value of two-dimensional layouts with multiple regions and user control of link visibility, we conducted a design-oriented, preliminary case study with 6 domain experts over a 4-month period. The main benefits were being able (a) to easily identify key papers and see the increasing number of papers within a research front, and (b) to quickly see the strength and direction of influence across related research fronts.
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.11, S.2219-2228
  19. Li, T.-C.: Reference sources in periodicals : research note (1995) 0.09
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    Abstract
    Presents a list of 53 periodicals in 22 subject fields which regularly provide bibliographies of theses, research in progress and patents in their particular subject field. The fields of business, economics, history and literature have most periodical listings of dissertations and theses. Also lists 63 periodicals in 25 sub-disciplines which provide rankings or ratings. Rankings and ratings information predominates in the fields of business, sports and games, finance and banking, and library and information science
    Source
    Journal of information; communication; and library science. 2(1995) no.2, S.20-28
  20. Tijssen, R.J.W.; Wijk, E. van: ¬The global science base of information and communication technologies : bibliometric analysis of ICT research papers (1998) 0.09
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    Abstract
    International bibliographic databases and related biblimetric indicators together provide an analytical framework and appropriate measure to cover both the 'supply side' - research capabilities and outputs - and 'demand side' - collaboration, diffusion and citation impact - related to information and communication technologies (ICT) research. Presents results of such a bibliometric study describing macro level features of this ICT knowledge base
    Date
    22. 5.1999 19:26:54

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