Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 04. Juni 2021)
1Franceschet, M.: ¬The large-scale structure of journal citation networks.
In: Journal of the American Society for Information Science and Technology. 63(2012) no.4, S.837-842.
Abstract: We analyze the large-scale structure of the journal citation network built from information contained in the Thomson-Reuters Journal Citation Reports. To this end, we explore network properties such as density, percolation robustness, average and largest node distances, reciprocity, incoming and outgoing degree distributions, and assortative mixing by node degrees. We discover that the journal citation network is a dense, robust, small, and reciprocal world. Furthermore, in- and outdegree node distributions display long tails, with few vital journals and many trivial ones, and they are strongly positively correlated.
Objekt: Journal Citation Reports
2Franceschet, M.: Collaboration in computer science : a network science approach.
In: Journal of the American Society for Information Science and Technology. 62(2011) no.10, S.1992-2012.
Abstract: Co-authorship in publications within a discipline uncovers interesting properties of the analyzed field. We represent collaboration in academic papers of computer science in terms of differently grained networks, namely affiliation and collaboration networks. We also build those sub-networks that emerge from either conference or journal co-authorship only. We take advantage of the network science paraphernalia to take a picture of computer science collaboration including all papers published in the field since 1936. Furthermore, we observe how collaboration in computer science evolved over time since 1960. We investigate bibliometric properties such as size of the discipline, productivity of scholars, and collaboration level in papers, as well as global network properties such as reachability and average separation distance among scholars, distribution of the number of scholar collaborators, network resilience and dependence on star collaborators, network clustering, and network assortativity by number of collaborators.
3Franceschet, M.: ¬A cluster analysis of scholar and journal bibliometric indicators.
In: Journal of the American Society for Information Science and Technology. 60(2009) no.10, S.1950-1964.
Abstract: We investigate different approaches based on correlation analysis to reduce the complexity of a space of quantitative indicators for the assessment of research performance. The proposed methods group bibliometric indicators into clusters of highly intercorrelated indicators. Each cluster is then associated with a representative indicator. The set of all representatives corresponds to a base of orthogonal metrics capturing independent aspects of research performance and can be exploited to design a composite performance indicator. We apply the devised methodology to isolate orthogonal performance metrics for scholars and journals in the field of computer science and to design a global performance indicator. The methodology is general and can be exploited to design composite indicators that are based on a set of possibly overlapping criteria.