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A bibliometric model for identifying emerging research topics
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.), Sustainability and Industrial Dynamics.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Detecting emerging research topics is essential, not only for research agencies but also for individual researchers. Previous studies have created various bibliographic indicators for the identification of emerging research topics. However, as indicated by Rotolo et al. (2015), the most serious problems are the lack of an acknowledged definition of emergence and incomplete elaboration of the linkages between the definitions that are used and the indicators that are created. With these issues in mind, this study first adjusts the definition of an emerging technology that Rotolo et al. (2015) have proposed in order to accommodate the analysis. Next, a set of criteria for the identification of emerging topics is proposed according to the adjusted definition and attributes of emergence. Using two sets of parameter values, several emerging research topics are identified. Finally, evaluation tests are conducted by the demonstration of the proposed approach and comparison with previous studies. The strength of the present methodology lies in the fact that it is fully transparent, straightforward, and flexible.

Keyword [en]
emerging research topics, identification, bibliometric analysis, definition, attributions, operationalization
National Category
Other Computer and Information Science
URN: urn:nbn:se:kth:diva-184729OAI: diva2:916732

QC 20160405

Available from: 2016-04-04 Created: 2016-04-04 Last updated: 2016-04-06Bibliographically approved
In thesis
1. Studies in the Dynamics of Science: Exploring emergence, classification, and interdisciplinarity
Open this publication in new window or tab >>Studies in the Dynamics of Science: Exploring emergence, classification, and interdisciplinarity
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The dynamic nature of science is embodied in the growth of knowledge in magnitude and the transformation of knowledge in structure. More specifically, the growth in magnitude is indicated by a sharp increase in the number of scientific publications in recent decades. The transformation of knowledge occurs as the boundaries of scientific disciplines become increasingly less distinct, resulting in a complicated situation wherein disciplines and interdisciplinary research topics coexist and co-evolve. Knowledge production in such a context creates challenges for the measurement of science.This thesisaims to develop more flexible bibliometric methodologies in order to address some of the challenges to measuring science effectively. To be specific, this thesis1) proposes a new approach for identifying emerging research topics; 2) measuresthe interdisciplinarity of research topics; 3) explores the accuracy of the journal classification systems of the Web of Science and Scopus; 4) examines the role of cognitive distance in grant decisions; and 5) investigates the effect of cognitive distance between collaborators on their research output. The data used in this thesisaremainly from the in-house Web of Science and Scopus databases of the Centre for Science and Technology Studies (CWTS) at Leiden University. Quantitativeanalyses, in particular bibliometric analyses,are the main research methodologies employed in this thesis. Furthermore, this thesis primarily offers methodological contributions, proposing a series of approaches designed to tackle the challenges created by the dynamics of science. While the major contribution of this dissertation lies in the improvement of certain bibliometric approaches, it also enhances the understanding of the current system of science. In particular, the approaches and research findings presented here have implications for various stakeholders, including publishing organizations, bibliographic database producers, research policy makers, and research funding agencies. Indeed, these approaches could be built into a software tool and thereby be made available to researchers beyond the field of bibliometric studies.

Place, publisher, year, edition, pages
Stockholm, Sweden: KTH Royal Institute of Technology, 2016. viii, 48 p.
TRITA-IEO, ISSN 1100-7982 ; 2016:04
science dynamics, bibliometrics, emerging research topics, interdisciplinary research, journal classification systems, cognitive distance, research policy
National Category
Social Sciences Interdisciplinary
urn:nbn:se:kth:diva-184724 (URN)1100-7982 (ISBN)
Public defence
2016-04-29, Sal F3, Lindstedtsvägen 26, KTH Campus, Stockholm, 10:00 (English)

QC 20160406

Available from: 2016-04-06 Created: 2016-04-04 Last updated: 2016-04-06Bibliographically approved

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