A bottom-up approach to assess the interdisciplinarity of journals from a multidisciplinary corpus of bibliographical records
| Autor: | Roche, Ivana, Besagni, Dominique, François, Claire, Hörlesberger, Marianne, Schiebel, Edgar L |
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| Přispěvatelé: | Institut de l'information scientifique et technique (INIST), Centre National de la Recherche Scientifique (CNRS), Austrian Research Centers GmbH (ARCS), ARCS, Gautier, Patricia |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
[STAT.AP]Statistics [stat]/Applications [stat.AP]
[STAT.AP] Statistics [stat]/Applications [stat.AP] [SHS.INFO]Humanities and Social Sciences/Library and information sciences InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Infométrie Interdisciplinarité Périodique scientifique et technique [SHS.INFO] Humanities and Social Sciences/Library and information sciences |
| Zdroj: | S&TI-ENID 2013 S&TI-ENID 2013, Sep 2013, Berlin, Germany |
| Popis: | International audience; This work is investigating the possibility of assessing the interdisciplinarity of scientific and technological journals without using any taxonomy or classification scheme as those usually adopted in bibliographical databases. For that, we start from a large corpus of bibliographic records from which we extract terms, either keywords already present or obtained by text mining techniques. With the help of a clustering method, that corpus is split into clusters defining a given number of scientific fields. Those fields and the keywords indexing each document are the basis of the calculation of an interdisciplinarity score applying the diffusion model approach. Then, we calculate an interdisciplinarity indicator for each journal by combining the scores obtained by its articles. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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