Search (212 results, page 1 of 11)

  • × theme_ss:"Informetrie"
  1. Herb, U.; Beucke, D.: ¬Die Zukunft der Impact-Messung : Social Media, Nutzung und Zitate im World Wide Web (2013) 0.10 
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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.
  2. Kumar, S.: Co-authorship networks : a review of the literature (2015) 0.07 
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    Abstract
    Purpose - The purpose of this paper is to attempt to provide a review of the growing literature on co-authorship networks and the research gaps that may be investigated for future studies in this field. Design/methodology/approach - The existing literature on co-authorship networks was identified, evaluated and interpreted. Narrative review style was followed. Findings - Co-authorship, a proxy of research collaboration, is a key mechanism that links different sets of talent to produce a research output. Co-authorship could also be seen from the perspective of social networks. An in-depth analysis of such knowledge networks provides an opportunity to investigate its structure. Patterns of these relationships could reveal, for example, the mechanism that shapes our scientific community. The study provides a review of the expanding literature on co-authorship networks. Originality/value - This is one of the first comprehensive reviews of network-based studies on co-authorship. The field is fast evolving, opening new gaps for potential research. The study identifies some of these gaps.
    Date
    20. 1.2015 18:30:22
  3. Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.06 
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    Abstract
    This article aims to identify whether different weighted PageRank algorithms can be applied to author citation networks to measure the popularity and prestige of a scholar from a citation perspective. Information retrieval (IR) was selected as a test field and data from 1956-2008 were collected from Web of Science. Weighted PageRank with citation and publication as weighted vectors were calculated on author citation networks. The results indicate that both popularity rank and prestige rank were highly correlated with the weighted PageRank. Principal component analysis was conducted to detect relationships among these different measures. For capturing prize winners within the IR field, prestige rank outperformed all the other measures
    Date
    22. 1.2011 13:02:21
  4. Milard, B.; Pitarch, Y.: Egocentric cocitation networks and scientific papers destinies (2023) 0.06 
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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
  5. Ding, Y.; Yan, E.: Scholarly network similarities : how bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other (2012) 0.06 
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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.
  6. Shibata, N.; Kajikawa, Y.; Takeda, Y.; Matsushima, K.: Comparative study on methods of detecting research fronts using different types of citation (2009) 0.04 
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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
  7. Zitt, M.; Lelu, A.; Bassecoulard, E.: Hybrid citation-word representations in science mapping : Portolan charts of research fields? (2011) 0.04 
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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
  8. Leydesdorff, L.: Can networks of journal-journal citations be used as indicators of change in the social sciences? (2003) 0.04 
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    Date
    6.11.2005 19:02:22
  9. Didegah, F.; Thelwall, M.: Co-saved, co-tweeted, and co-cited networks (2018) 0.04 
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    Date
    28. 7.2018 10:00:22
  10. Mulkay, M.J.; Gilbert, G.N.; Woolgar, S.: Problem areas and research networks in science (1975) 0.03 
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  11. Zhao, S.X.; Zhang, P.L.; Li, J.; Tan, A.M.; Ye, F.Y.: Abstracting the core subnet of weighted networks based on link strengths (2014) 0.03 
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    Abstract
    Most measures of networks are based on the nodes, although links are also elementary units in networks and represent interesting social or physical connections. In this work we suggest an option for exploring networks, called the h-strength, with explicit focus on links and their strengths. The h-strength and its extensions can naturally simplify a complex network to a small and concise subnetwork (h-subnet) but retains the most important links with its core structure. Its applications in 2 typical information networks, the paper cocitation network of a topic (the h-index) and 5 scientific collaboration networks in the field of "water resources," suggest that h-strength and its extensions could be a useful choice for abstracting, simplifying, and visualizing a complex network. Moreover, we observe that the 2 informetric models, the Glänzel-Schubert model and the Hirsch model, roughly hold in the context of the h-strength for the collaboration networks.
  12. Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006) 0.03 
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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
  13. Meho, L.I.; Rogers, Y.: Citation counting, citation ranking, and h-index of human-computer interaction researchers : a comparison of Scopus and Web of Science (2008) 0.03 
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    Abstract
    This study examines the differences between Scopus and Web of Science in the citation counting, citation ranking, and h-index of 22 top human-computer interaction (HCI) researchers from EQUATOR - a large British Interdisciplinary Research Collaboration project. Results indicate that Scopus provides significantly more coverage of HCI literature than Web of Science, primarily due to coverage of relevant ACM and IEEE peer-reviewed conference proceedings. No significant differences exist between the two databases if citations in journals only are compared. Although broader coverage of the literature does not significantly alter the relative citation ranking of individual researchers, Scopus helps distinguish between the researchers in a more nuanced fashion than Web of Science in both citation counting and h-index. Scopus also generates significantly different maps of citation networks of individual scholars than those generated by Web of Science. The study also presents a comparison of h-index scores based on Google Scholar with those based on the union of Scopus and Web of Science. The study concludes that Scopus can be used as a sole data source for citation-based research and evaluation in HCI, especially when citations in conference proceedings are sought, and that researchers should manually calculate h scores instead of relying on system calculations.
  14. Thelwall, M.; Sud, P.; Wilkinson, D.: Link and co-inlink network diagrams with URL citations or title mentions (2012) 0.03 
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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
  15. Thelwall, M.; Kousha, K.; Abdoli, M.; Stuart, E.; Makita, M.; Wilson, P.; Levitt, J.: Why are coauthored academic articles more cited : higher quality or larger audience? (2023) 0.03 
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    Abstract
    Collaboration is encouraged because it is believed to improve academic research, supported by indirect evidence in the form of more coauthored articles being more cited. Nevertheless, this might not reflect quality but increased self-citations or the "audience effect": citations from increased awareness through multiple author networks. We address this with the first science wide investigation into whether author numbers associate with journal article quality, using expert peer quality judgments for 122,331 articles from the 2014-20 UK national assessment. Spearman correlations between author numbers and quality scores show moderately strong positive associations (0.2-0.4) in the health, life, and physical sciences, but weak or no positive associations in engineering and social sciences, with weak negative/positive or no associations in various arts and humanities, and a possible negative association for decision sciences. This gives the first systematic evidence that greater numbers of authors associates with higher quality journal articles in the majority of academia outside the arts and humanities, at least for the UK. Positive associations between team size and citation counts in areas with little association between team size and quality also show that audience effects or other nonquality factors account for the higher citation rates of coauthored articles in some fields.
    Date
    22. 6.2023 18:11:50
  16. Pepe, A.: ¬The relationship between acquaintanceship and coauthorship in scientific collaboration networks (2011) 0.03 
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    Abstract
    This article examines the relationship between acquaintanceship and coauthorship patterns in a multi-disciplinary, multi-institutional, geographically distributed research center. Two social networks are constructed and compared: a network of coauthorship, representing how researchers write articles with one another, and a network of acquaintanceship, representing how those researchers know each other on a personal level, based on their responses to an online survey. Statistical analyses of the topology and community structure of these networks point to the importance of small-scale, local, personal networks predicated upon acquaintanceship for accomplishing collaborative work in scientific communities.
  17. Zhang, H.; Qiu, B.; Ivanova, K.; Giles, C.L.; Foley, H.C.; Yen, J.: Locality and attachedness-based temporal social network growth dynamics analysis : a case study of evolving nanotechnology scientific collaboration networks (2010) 0.03 
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    Abstract
    The rapid advancement of nanotechnology research and development during the past decade presents an excellent opportunity for a scientometric study because it can provide insights into the dynamic growth of the fast-evolving social networks associated with this field. In this article, we describe a case study conducted on nanotechnology to discover the dynamics that govern the growth process of rapidly advancing scientific-collaboration networks. This article starts with the definition of temporal social networks and demonstrates that the nanotechnology collaboration network, similar to other real-world social networks, exhibits a set of intriguing static and dynamic topological properties. Inspired by the observations that in collaboration networks new connections tend to be augmented between nodes in proximity, we explore the locality elements and the attachedness factor in growing networks. In particular, we develop two distance-based computational network growth schemes, namely the distance-based growth model (DG) and the hybrid degree and distance-based growth model (DDG). The DG model considers only locality element while the DDG is a hybrid model that factors into both locality and attachedness elements. The simulation results from these models indicate that both clustering coefficient rates and the average shortest distance are closely related to the edge densification rates. In addition, the hybrid DDG model exhibits higher clustering coefficient values and decreasing average shortest distance when the edge densification rate is fixed, which implies that combining locality and attachedness can better characterize the growing process of the nanotechnology community. Based on the simulation results, we conclude that social network evolution is related to both attachedness and locality factors.
  18. Lee, K.; Kim, S.Y.; Kim, E.H.-J.; Song, M.: Comparative evaluation of bibliometric content networks by tomographic content analysis : an application to Parkinson's disease (2017) 0.02 
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    Abstract
    To understand the current state of a discipline and to discover new knowledge of a certain theme, one builds bibliometric content networks based on the present knowledge entities. However, such networks can vary according to the collection of data sets relevant to the theme by querying knowledge entities. In this study we classify three different bibliometric content networks. The primary bibliometric network is based on knowledge entities relevant to a keyword of the theme, the secondary network is based on entities associated with the lower concepts of the keyword, and the tertiary network is based on entities influenced by the theme. To explore the content and properties of these networks, we propose a tomographic content analysis that takes a slice-and-dice approach to analyzing the networks. Our findings indicate that the primary network is best suited to understanding the current knowledge on a certain topic, whereas the secondary network is good at discovering new knowledge across fields associated with the topic, and the tertiary network is appropriate for outlining the current knowledge of the topic and relevant studies.
  19. Scharnhorst, A.: Citation - networks, science landscapes and evolutionary strategies (1998) 0.02 
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    Abstract
    The construction of virtual science landscapes based on citation networks and the strategic use of the information therein shed new light on the issues of the evolution of the science system and possibilities for control. Leydesdorff's approach to citation theory described in his 1998 article (see this issue of LISA) takes into account the dual layered character of communication networks and the second order nature of the science system. This perspective may help to sharpen the awareness of scientists and science policy makers for possible feedback loops within actions and activities in the science system, and probably nonlinear phenomena resulting therefrom. Sketches an additional link to geometrically oriented evolutionary theories and uses a specific landscape concept as a framework for some comments
  20. Stock, W.G.: Wirtschaftsinformationen aus informetrischen Online-Recherchen (1992) 0.02 
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    Abstract
    Online databases can be used for statistical analysis, creating new information. Discusses 4 methods applied to economic information: time series, rankings, semantic networks, and graphs of information flow

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