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+ | ====== 1214. sredin seminar, 20. junij 2012 ====== | ||
+ | Gomez Nuñez, Antonio Jesus <antoniojesus.gomez@cchs.csic.es> | ||
+ | **Improving the Categorization of Scopus Journals included in SCImago Journal & Country Rank (SJR)** | ||
+ | |||
+ | |||
+ | Scientific information stored in large scientific multidisciplinary | ||
+ | databases requires a good organization and arrangement not only for | ||
+ | information retrieval purposes but for developing reliable and | ||
+ | non-misleading indicators about impact, collaboration, visibility..., | ||
+ | within disciplines like Bibliometrics and Scientometrics. Similarly, a | ||
+ | good classification of information, regardless of aggregation level, | ||
+ | is desirable for information visualization or network analysis, whose | ||
+ | main surveys are based on information covered by scientific databases. | ||
+ | Among the most prestigious and remarkable ones are Web of Knowledge | ||
+ | (WOK) [Thomson Reuters] and Scopus [Elsevier]. Both use a similar | ||
+ | classification scheme according to a hierarchical system in two levels | ||
+ | composed of areas (broad level) and categories (specific level). | ||
+ | |||
+ | Among different tools for analysis and assessment of scientific | ||
+ | information "SCImago Journal & Country Rank is a portal that includes | ||
+ | the journals and country scientific indicators developed from the | ||
+ | information contained in the Scopus® database (Elsevier B.V.). These | ||
+ | indicators can be used to assess and analyze scientific domains" | ||
+ | (Scimago Lab. http://www.scimagojr.com/). Starting from the previous | ||
+ | classification of journals produced by Scopus, the categorization of | ||
+ | journals was refined following different criteria like opinion of | ||
+ | experts, tiles and scopes of journals. | ||
+ | |||
+ | Hereupon, it was pretended to improve and to tune the categorization | ||
+ | of the SJR journal set using automatic and statistical procedures, or | ||
+ | at least, avoiding the human mediation so far as possible. Thus, a | ||
+ | first work to improve the classification scheme of SJR working from | ||
+ | initial categorization and using reference analysis in combination | ||
+ | with different citation thresholds to determine the final category of | ||
+ | every journal was implemented. This method showed a solid performance | ||
+ | in grouping journals at a level higher than categories —that is, | ||
+ | aggregating journals into subject areas. It also enabled us to | ||
+ | redesign the SJR classification scheme, providing for a more cohesive | ||
+ | one that covers a good proportion of re-categorized journals. Anyhow, | ||
+ | in order to obtain a better categorization of journals, the method | ||
+ | should be complemented with additional techniques. | ||
+ | |||
+ | For following work, it was decided to make clustering of journals | ||
+ | using a combination of three citation measures, namely, Direct | ||
+ | Citation (DC), Cocitation (CC) and Bibliographic Coupling (BC). | ||
+ | Using R statistical software, an asymmetrical journal-journal matrix | ||
+ | with the sum of fractionalized 3-citation-measures was constructed | ||
+ | and then, values were transformed into cosine similarities. In | ||
+ | closing, similarities values were transformed into distances and | ||
+ | Ward hierarchical clustering was applied on them. | ||
+ | |||
+ | The proposal to develop in Ljubljana is related to the use of | ||
+ | software Pajek and, concretely, island analysis to detect different | ||
+ | sub-networks (clusters) from the global journal citation network | ||
+ | formed by around 19000 Scopus journals. | ||
+ | |||
+ | For the future research, it seems interesting to employ new | ||
+ | statistical/automatic techniques or network analysis adopting a | ||
+ | combination of different variables like citation measures, text of | ||
+ | documents (title, abstract and/or keywords), or address of authors, | ||
+ | etc. | ||
+ | |||
+ | [[vlado:pub:sreda|Sreda/wiki]] |