Search (3 results, page 1 of 1)

  • × author_ss:"Morris, S.A."
  • × theme_ss:"Informetrie"
  1. Morris, S.A.; Yen, G.; Wu, Z.; Asnake, B.: Time line visualization of research fronts (2003) 0.01 
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  2. Morris, S.A.: Manifestation of emerging specialties in journal literature : a growth model of papers, references, exemplars, bibliographic coupling, cocitation, and clustering coefficient distribution (2005) 0.00 
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    Abstract
    A model is presented of the manifestation of the birth and development of a scientific specialty in a collection of journal papers. The proposed model, Cumulative Advantage by Paper with Exemplars (CAPE) is an adaptation of Price's cumulative advantage model (D. Price, 1976). Two modifications are made: (a) references are cited in groups by paper, and (b) the model accounts for the generation of highly cited exemplar references immediately after the birth of the specialty. This simple growth process mimics many characteristic features of real collections of papers, including the structure of the paper-to-reference matrix, the reference-per-paper distribution, the paper-per-reference distribution, the bibliographic coupling distribution, the cocitation distribution, the bibliographic coupling clustering coefficient distribution, and the temporal distribution of exemplar references. The model yields a great deal of insight into the process that produces the connectedness and clustering of a collection of articles and references. Two examples are presented and successfully modeled: a collection of 131 articles an MEMS RF (microelectromechnical systems radio frequency) switches, and a collection of 901 articles an the subject of complex networks.
  3. Morris, S.A.; Goldstein, M.L.: Manifestation of research teams in journal literature : a growth model of papers, authors, collaboration, coauthorship, weak ties, and Lotka's law (2007) 0.00 
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    Abstract
    This article introduces a team-based model of researchers in a specialty and investigates the manifestation of such teams in a specialty's literature. The proposed qualitative behavioral model, with its mathematical expression as a growth model, is significant because it simultaneously describes the two phenomena of collaboration and author productivity (Lotka's law) in a specialty. The model is nested: A team process models the creation of research teams and the success-breeds-success process of their production of articles, while at a lower level the productivity of authors within teams is also modeled as a success-breeds-success process. Interteam collaboration (weak ties) is modeled as random events. This simple growth model is shown to faithfully mimic six network metrics of bipartite article-author networks. The model is demonstrated on three example article collections from specialties that have a wide range of degree of collaboration: (a) a distance education collection with low collaboration degree, (b) a complex networks collection with typical collaboration degree, and (c) an atrial ablation collection with heavy collaboration degree.

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