Chang network analysis


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Chang network analysis

  1. 1. A Network Analysis of Interdisciplinary Research Relationships: the Korean Government’s R&D Grant Program Chang Hoon Yang, Ph.D. Department of Public Administration Kwandong University
  2. 2. Table of Contents <ul><li>Research Object </li></ul><ul><li>Underlying Assumptions </li></ul><ul><li>Methodological Approach </li></ul><ul><li>Related Studies </li></ul><ul><li>Utilization of Network Analysis </li></ul><ul><li>Implications and Discussion </li></ul>
  3. 3. Research Object <ul><li>Examines network topologies of interdisciplinary research relationships in S&T </li></ul><ul><li>Investigates the relational linkages between the interdisciplinary relations and the quality of research performance </li></ul><ul><li>2002-2004 KOSEF General Research Grant program [ 중견연구자사업 중 핵심연구 ( 공동 ) 사업 ] </li></ul><ul><li>Network method - matrix of the co-occurrence of research fields in the classification of research articles </li></ul>
  4. 4. Underlying Assumptions <ul><li>Individual scientists </li></ul><ul><ul><li>No longer independent components of a national system of research, technology, and innovation </li></ul></ul><ul><li>Competitive advantage could be secured through cooperative partnerships </li></ul><ul><ul><li>Exchange various levels of scientific and technological capabilities and expertise </li></ul></ul><ul><ul><li>Produce new scientific output classified into more than one field </li></ul></ul><ul><li>Cooperative research activities as a means to </li></ul><ul><ul><li>enhance capacity building among actors </li></ul></ul><ul><ul><li>foster interdisciplinary linkages among research fields in the integrated S&T arena </li></ul></ul>
  5. 5. Methodological Approach <ul><li>Forms of relationships constituting networks </li></ul><ul><ul><li>Clusters of research fields relating to each other </li></ul></ul><ul><ul><li>Interdisciplinary structure emerging between research fields </li></ul></ul><ul><li>Basis for a relational linking process </li></ul><ul><ul><li>co-occurrence of classifications of articles </li></ul></ul><ul><li>Network analytical tools </li></ul><ul><ul><li>A field co-occurrence mapping method </li></ul></ul><ul><ul><li>comparing similarities in research profiles of co-authored articles </li></ul></ul>
  6. 6. Related Studies <ul><li>Archibugi & Pianta (1992) </li></ul><ul><ul><li>Patent counts and citations for measuring technological specialization profiles </li></ul></ul><ul><li>Braun, Gomez, Mendez, Schubert (1992) </li></ul><ul><ul><li>Co-authorship patterns in a scientific discipline and its subfields </li></ul></ul><ul><li>Bonitz, Bruckner, Scharnhorst (1993) </li></ul><ul><ul><li>Publication output structure of countries and clusters of countries with similar structures </li></ul></ul><ul><li>Glanzel & Schubert (2003) </li></ul><ul><ul><li>Subject categories for retrieving discipline information </li></ul></ul><ul><li>Cummings & Kiesler (2005) </li></ul><ul><ul><li>Project with PI from more than one discipline </li></ul></ul><ul><li>Leydesdorff (2008) </li></ul><ul><ul><li>Co-classification analysis using patent portfolio </li></ul></ul>
  7. 7. Utilization of Network Analysis <ul><li>Dataset </li></ul><ul><ul><li>Characterizing interdependent research activities </li></ul></ul><ul><ul><li>1,108 articles published in SCI-listed journals and funded by GRG program </li></ul></ul><ul><ul><li>Contained one area of PI specialization (=PI-based subject category) </li></ul></ul><ul><ul><li>JCR-based field classification for articles (=research field) </li></ul></ul>
  8. 8. Two-mode Matrix of co-occurrence <ul><li>Row: research field (99 observations) </li></ul><ul><li>Column: PI-based subject category (51 observations) </li></ul><ul><li>Nodes: research fields </li></ul><ul><ul><li>be linked if they contain the same PI-based subject category </li></ul></ul><ul><li>Interdisciplinary network : </li></ul><ul><ul><li>R k = 1 if R ij:k = 1 and 0 otherwise </li></ul></ul><ul><ul><li>R ij:k number of articles where research field i and j classify in the same PI-based subject category k </li></ul></ul><ul><li>Symmetric one-mode matrix for research fields </li></ul><ul><ul><li>by multiplying two-mode matrix by its transposes </li></ul></ul>
  9. 9. Analytical Techniques <ul><li>Interdisciplinary relations weighted by the location of interdisciplinary research fields </li></ul><ul><li>Cohesion </li></ul><ul><ul><li>length of shortest path between two nodes </li></ul></ul><ul><ul><li>Number of relations in the shortest possible relations from one research field to another </li></ul></ul><ul><li>Centrality </li></ul><ul><ul><li>the extent to which nodes are connected to other nodes </li></ul></ul><ul><ul><li>Degree: number of interdisciplinary relations created across the research fields </li></ul></ul><ul><ul><li>Betweenness: the extent to which a particular research field lies as an intermediary between other interdisciplinary research fields </li></ul></ul><ul><li>Egocentric network </li></ul><ul><ul><li>Degree to which particular research fields are involved in a network at the single level </li></ul></ul><ul><ul><li>Topologies of networks in which single research fields are bound with their neighboring research fields </li></ul></ul>
  10. 10. Analytical Techniques (cont’d) <ul><li>Understanding the extent to which topologies of interdisciplinary networks in different research fields are related to research quality </li></ul><ul><ul><li>Correlation between degree centrality and the relative impact factor (RIF) </li></ul></ul><ul><ul><li>RIF : a journal’s place and impact within a specific discipline </li></ul></ul><ul><ul><li>as (A/B)*100, A is rank of a journal within a specific subject category and B is number of journals belonging to the specific subject category </li></ul></ul><ul><ul><li>Assess quality of interdisciplinary research supported by GRG program </li></ul></ul>
  11. 11. Example: Network centralization in interdisciplinary relations
  12. 12. Example: Egocentric network of chemistry, multidisciplinary
  13. 13. Example: Relationship between research collaboration and research productivity Degree centrality (log x) versus RIF (y)
  14. 14. Implications & Discussion
  15. 15. End of Presentation Thank You