The Social Contexts of Research. Edited by Saad Z. Nagi and Ronald G. Corwin. Pp. xii + 409. (John Wiley: New York and London, August 1972.) £5.65.

Sociology of Science

The goal of this paper is to show how co-word analysis techniques can be used to study interactions between academic and technological research. It is based upon a systematic content analysis of publications in the polymer science field over a period of 15 years. The results concern a.) the evolution of research in different subject areas and the patterns of their interaction; b.) a description of subject area “life cycles”; c.) an analysis of ”research trajectories” given factors of stability and change in a research network; d.) the need to use both science push and technology pull theories to explain the interaction dynamics of a research field. The co-word techniques developed in this paper should help to build a bridge between research in scientometrics and work underway to better understand the economics of innovation.

Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry

Social Stratification in Science

The claim that co-citation analysis is a useful tool to map subject-matter specialties of scientific research in a given period, is examined. A method has been developed using quantitative analysis of content-words related to publications in order to: (1) study coherence of research topics within sets of publications citing clusters, i.e., (part of) the “current work” of a specialty; (2) to study differences in research topics between sets of publications citing different clusters; and (3) to evaluate recall of “current work” publications concerning the specialties identified by co-citation analysis. Empirical support is found for the claim that co-citation analysis identifies indeed subject-matter specialties. However, different clusters may identify the same specialty, and results are far from complete concerning the identified “current work.” These results are in accordance with the opinion of some experts in the fields. Low recall of co-citation analysis concerning the “current work” of specialties is shown to be related to the way in which researchers build their work on earlier publications: the “missed” publications equally build on very recent earlier work, but are less “consensual” and/or less “attentive” in their referencing practice. Evaluation of national research performance using co-citation analysis appears to be biased by this “incompleteness.”

/pdf/mapping-of-science-by-combined-co-citation-and-word-analysis-58tyfviibw.pdf

Mapping of Science by Combined Co-Citation and Word Analysis. I. Structural Aspects

Traditional citation analysis has been widely applied to detect patterns of scientific collaboration, map the landscapes of scholarly disciplines, assess the impact of research outputs, and observe knowledge transfer across domains. It is, however, limited, as it assumes all citations are of similar value and weights each equally. Content-based citation analysis (CCA) addresses a citation’s value by interpreting each one based on its context at both the syntactic and semantic levels. This paper provides a comprehensive overview of CAA research in terms of its theoretical foundations, methodical approaches, and example applications. In addition, we highlight how increased computational capabilities and publicly available full-text resources have opened this area of research to vast possibilities, which enable deeper citation analysis, more accurate citation prediction, and increased knowledge discovery.

http://info.slis.indiana.edu/~dingying/Publication/CCA-final.pdf

Content-Based Citation Analysis: The Next Generation of Citation Analysis

Summary Studies of science and technology have used the social network concept beginning with the idea of a “scientific community.” An increase in the use of quantitative network analysis has characterized the past two decades, as techniques have diffused into the field from mainstream sociology and from communication research. Three main classes of studies are considered: (1) those which focus on intra-organizational ties; (2) those which focus on interorganizational relations (including quantitative studies of “specialties”); (3) bibliometric networks (linkages of technical products rather than personnel). Our review of network approaches illustrates their power and generality but reveals serious deficiencies at all levels of analysis.

Network analysis in the study of science and technology

We analyze the structural elements which comprise a standard scientific paper. Previous analysis generally has focused on one element of a paper at a time. However, the title, author list, affiliation, abstract, text, tables, graphs, charts, photographs and references all represent possible data resources for investigation. After specifying those elements, we focus successively on the history, normative tradition, and sociological analysis of a selection of those elements.

The structural analysis of a scientific paper

The citation rates of scientific papers, long used by numerous sociologists of science to measure the influence of individual scientists and the diffusion of knowledge, are shown to be partly affected by the various structural characteristics of these papers. Based on an analysis of 221 scientific papers in three cocitation clusters, between 15 and 35 percent of the variation in citation rates is found to be a function of those papers' textual and nontextual characteristics. The citation rates of papers in the Burkitts-Lymphoma and Heavy Quark Potential clusters are shown to be heavily dependent on abstract characteristics such as readability and number of uncommon words. The citation rates of DNA cluster papers are observed to be significantly affected by both the number of references and figures found in teh body of those papers. Of particular note is the fact that while the readability of abstracts is shown to decrease the citation rates of Burkitts-Lymphoma papers, the opposite is true of Heavy Quark Potential papers.

Textual and nontextual characteristics of scientific papers: Neglected science indicators

Evaluating research programs: measurement and data sources

An intensive investigation of the American science advisory system failed to find indications of elite structure in the selection or patterns of service of advisors. Advisory groups cannot act as elements of the invisible college circuits thatPrice refered to. The only long term advisors areex officio members. Advisory committee growth and activity is marked by three periods: 1951 to 1957, slow growth; 1957 to 1966, rapid growth; and 1967 to 1972, no growth. Combined with the pattern of growth in numbers of eligible scientists, a perception of elite control may have been created.

Nicholas C. Mullins

Papers

Network analysis in the study of science and technology

The structural analysis of a scientific paper

Textual and nontextual characteristics of scientific papers: Neglected science indicators

Evaluating research programs: measurement and data sources

Invisible colleges as science elites