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  • × theme_ss:"Informetrie"
  1. Yan, E.; Yu, Q.: Using path-based approaches to examine the dynamic structure of discipline-level citation networks (2016) 0.05
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    Abstract
    The objective of this paper is to identify the dynamic structure of several time-dependent, discipline-level citation networks through a path-based method. A network data set is prepared that comprises 27 subjects and their citations aggregated from more than 27,000 journals and proceedings indexed in the Scopus database. A maximum spanning tree method is employed to extract paths in the weighted, directed, and cyclic networks. This paper finds that subjects such as Medicine, Biochemistry, Chemistry, Materials Science, Physics, and Social Sciences are the ones with multiple branches in the spanning tree. This paper also finds that most paths connect science, technology, engineering, and mathematics (STEM) fields; 2 critical paths connecting STEM and non-STEM fields are the one from Mathematics to Decision Sciences and the one from Medicine to Social Sciences.
  2. Robinson, L.; Maguire, M.: ¬The rhizome and the tree : changing metaphors for information organisation (2010) 0.04
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  3. Newby, G.B.; Greenberg, J.; Jones, P.: Open source software development and Lotka's law : bibliometric patterns in programming (2003) 0.04
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    Abstract
    Newby, Greenberg, and Jones analyze programming productivity of open source software by counting registered developers contributions found in the Linux Software Map and in Scourceforge. Using seven years of data from a subset of the Linux directory tree LSM data provided 4503 files with 3341 unique author names. The distribution follows Lotka's Law with an exponent of 2.82 as verified by the Kolmolgorov-Smirnov one sample goodness of fit test. Scourceforge data is broken into developers and administrators, but when both were used as authors the Lotka distribution exponent of 2.55 produces the lowest error. This would not be significant by the K-S test but the 3.54% maximum error would indicate a fit and calls into question the appropriateness of K-S for large populations of authors.
  4. Leydesdorff, L.; Rotolo, D.; Rafols, I.: Bibliometric perspectives on medical innovation using the medical subject headings of PubMed (2012) 0.04
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    Abstract
    Multiple perspectives on the nonlinear processes of medical innovations can be distinguished and combined using the Medical Subject Headings (MeSH) of the MEDLINE database. Focusing on three main branches-"diseases," "drugs and chemicals," and "techniques and equipment"-we use base maps and overlay techniques to investigate the translations and interactions and thus to gain a bibliometric perspective on the dynamics of medical innovations. To this end, we first analyze the MEDLINE database, the MeSH index tree, and the various options for a static mapping from different perspectives and at different levels of aggregation. Following a specific innovation (RNA interference) over time, the notion of a trajectory which leaves a signature in the database is elaborated. Can the detailed index terms describing the dynamics of research be used to predict the diffusion dynamics of research results? Possibilities are specified for further integration between the MEDLINE database on one hand, and the Science Citation Index and Scopus (containing citation information) on the other.
  5. Chen, R.H.-G.; Chen, C.-M.: Visualizing the world's scientific publications (2016) 0.03
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    Abstract
    Automated methods for the analysis, modeling, and visualization of large-scale scientometric data provide measures that enable the depiction of the state of world scientific development. We aimed to integrate minimum span clustering (MSC) and minimum spanning tree methods to cluster and visualize the global pattern of scientific publications (PSP) by analyzing aggregated Science Citation Index (SCI) data from 1994 to 2011. We hypothesized that PSP clustering is mainly affected by countries' geographic location, ethnicity, and level of economic development, as indicated in previous studies. Our results showed that the 100 countries with the highest rates of publications were decomposed into 12 PSP groups and that countries within a group tended to be geographically proximal, ethnically similar, or comparable in terms of economic status. Hubs and bridging nodes in each knowledge production group were identified. The performance of each group was evaluated across 16 knowledge domains based on their specialization, volume of publications, and relative impact. Awareness of the strengths and weaknesses of each group in various knowledge domains may have useful applications for examining scientific policies, adjusting the allocation of resources, and promoting international collaboration for future developments.
  6. Jiang, X.; Zhu, X.; Chen, J.: Main path analysis on cyclic citation networks (2020) 0.03
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    Abstract
    Main path analysis is a famous network-based method for understanding the evolution of a scientific domain. Most existing methods have two steps, weighting citation arcs based on search path counting and exploring main paths in a greedy fashion, with the assumption that citation networks are acyclic. The only available proposal that avoids manual cycle removal is to preprint transform a cyclic network to an acyclic counterpart. Through a detailed discussion about the issues concerning this approach, especially deriving the "de-preprinted" main paths for the original network, this article proposes an alternative solution with two-fold contributions. Based on the argument that a publication cannot influence itself through a citation cycle, the SimSPC algorithm is proposed to weight citation arcs by counting simple search paths. A set of algorithms are further proposed for main path exploration and extraction directly from cyclic networks based on a novel data structure main path tree. The experiments on two cyclic citation networks demonstrate the usefulness of the alternative solution. In the meanwhile, experiments show that publications in strongly connected components may sit on the turning points of main path networks, which signifies the necessity of a systematic way of dealing with citation cycles.
  7. Ikae, C.; Savoy, J.: Gender identification on Twitter (2022) 0.03
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    Abstract
    To determine the author of a text's gender, various feature types have been suggested (e.g., function words, n-gram of letters, etc.) leading to a huge number of stylistic markers. To determine the target category, different machine learning models have been suggested (e.g., logistic regression, decision tree, k nearest-neighbors, support vector machine, naïve Bayes, neural networks, and random forest). In this study, our first objective is to know whether or not the same model always proposes the best effectiveness when considering similar corpora under the same conditions. Thus, based on 7 CLEF-PAN collections, this study analyzes the effectiveness of 10 different classifiers. Our second aim is to propose a 2-stage feature selection to reduce the feature size to a few hundred terms without any significant change in the performance level compared to approaches using all the attributes (increase of around 5% after applying the proposed feature selection). Based on our experiments, neural network or random forest tend, on average, to produce the highest effectiveness. Moreover, empirical evidence indicates that reducing the feature set size to around 300 without penalizing the effectiveness is possible. Finally, based on such reduced feature sizes, an analysis reveals some of the specific terms that clearly discriminate between the 2 genders.
  8. Nicholls, P.T.: Empirical validation of Lotka's law (1986) 0.03
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    Source
    Information processing and management. 22(1986), S.417-419
  9. Nicolaisen, J.: Citation analysis (2007) 0.03
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    Date
    13. 7.2008 19:53:22
  10. Fiala, J.: Information flood : fiction and reality (1987) 0.03
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    Source
    Thermochimica acta. 110(1987), S.11-22
  11. Su, Y.; Han, L.-F.: ¬A new literature growth model : variable exponential growth law of literature (1998) 0.02
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    Date
    22. 5.1999 19:22:35
  12. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.02
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    Date
    22. 7.2006 15:22:28
  13. Diodato, V.: Dictionary of bibliometrics (1994) 0.02
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    Footnote
    Rez. in: Journal of library and information science 22(1996) no.2, S.116-117 (L.C. Smith)
  14. Bookstein, A.: Informetric distributions : I. Unified overview (1990) 0.02
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    Date
    22. 7.2006 18:55:29
  15. Bookstein, A.: Informetric distributions : II. Resilience to ambiguity (1990) 0.02
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    Date
    22. 7.2006 18:55:55
  16. Lewison, G.: ¬The work of the Bibliometrics Research Group (City University) and associates (2005) 0.02
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    Date
    20. 1.2007 17:02:22
  17. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.02
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    Date
    18. 3.2014 19:13:22
  18. Raan, A.F.J. van: Statistical properties of bibliometric indicators : research group indicator distributions and correlations (2006) 0.01
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    Date
    22. 7.2006 16:20:22
  19. Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009) 0.01
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    Date
    22. 3.2009 19:22:35
  20. Li, T.-C.: Reference sources in periodicals : research note (1995) 0.01
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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

Years

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  • ro 1
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