Delineation of scientific domains (fields, areas of science) is a prior task in bibliometric studies at the meso-level, far from straightforward in domains with high multidisciplinarity, variety and instability. The Context section shows the connection of delineation problem to the question of disciplines vs. invisible colleges, through three combinable models: ready-made classifications of science, classical information retrieval searches, mapping and clustering. They differ in the role and modalities of supervision. The Tools section sketches various bibliometric techniques on the background of information retrieval, data analysis, network theory, showing both their power and their limitations in delineation processes. The role and modalities of supervision are emphasized. The section Multiple Networks and Hybridization addresses the comparison and combination of bibliometric networks (actors, texts, citations) and the various ways of hybridization. In the concluding section, typical protocols and further questions are proposed.
This article presents a citation-based mapping exercise in the nanosciences field and a first sketch of citation transactions (a measure of cognitive dependences). Nanosciences are considered to be one of the "convergent" components shaping the future of science and technology. Recurrent questions about the structure of the field concern its diversity and multi-or inter-disciplinarity. Observations made from various points of view confirm a strong differentiation of the field, which is scattered in multiple galaxies with moderate level of exchanges. The multi-disciplinarity of themes and super-themes detected by mapping also appears moderate, most of the super-themes being based on physics and chemistry in various proportions. Structural analysis of the list of references in articles suggests that the moderate multi-disciplinarity observed at the aggregate level partly stems from an actual inter-disciplinarity at the article level.
The mapping of scientific fields, based on principles established in the seventies, has recently shown a remarkable development and applications are now booming with progress in computing efficiency. We examine here the convergence of two thematic mapping approaches, citation-based and word-based, which rely on quite different sociological backgrounds. A corpus in the nanoscience field was broken down into research themes, using the same clustering technique on the 2 networks separately. The tool for comparison is the table of intersections of the M clusters (here M = 50) built on either side. A classical visual exploitation of such contingency tables is based on correspondence analysis. We investigate a rearrangement of the intersection table (block modeling), resulting in pseudo-map. The interest of this representation for confronting the two breakdowns is discussed. The amount of convergence found is, in our view, a strong argument in favor of the reliability of bibliometric mapping. However, the outcomes are not convergent at the degree where they can be substituted for each other. Differences highlight the complementarity between approaches based on different networks. In contrast with the strong informetric posture found in recent literature, where lexical and citation markers are considered as miscible tokens, the framework proposed here does not mix the two elements at an early stage, in compliance with their contrasted logic.
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