arXiv subjects

Raf Guns

Publications and source records attributed to Raf Guns.

6 recordsLinked to original sources

arXiv2025

Comparing Disciplinary Classifications in SSH: Organizational, Channel-Based, and Text-Based Perspectives

This study investigates how different approaches to disciplinary classification represent the Social Sciences and Humanities (SSH) in the Flemish VABB-SHW database. We compare organizational classification (based on author affiliation), channel-based cognitive classification (based on publication venues), and text-based publication-level classification (using channel titles, publication titles, and abstracts, depending on availability). The analysis shows that text-based classification generally aligns more closely with channel-based categories, confirming that the channel choice provides relevant information about publication content. At the same time, it is closer to organizational classification than channel-based categories are, suggesting that textual features capture author affiliations more directly than publishing channels do. Comparison across the three systems highlights cases of convergence and divergence, offering insights into how disciplines such as "Sociology" and "History" extend across fields, while "Law" remains more contained. Publication-level classification also clarifies the disciplinary profiles of multidisciplinary journals in the database, which in VABB-SHW show distinctive profiles with stronger emphases on SSH and health sciences. At the journal level, fewer than half of outlets with more than 50 publications have their channel-level classification fully or partially supported by more than 90% of publications. These results demonstrate the added value of text-based methods for validating classifications and for analysing disciplinary dynamics.

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arXiv2022

Towards indicating interdisciplinarity: Characterizing interdisciplinary knowledge flow

This study contributes to the recent discussions on indicating interdisciplinarity, i.e., going beyond catch-all metrics of interdisciplinarity. We propose a contextual framework to improve the granularity and usability of the existing methodology for interdisciplinary knowledge flow (IKF) in which scientific disciplines import and export knowledge from/to other disciplines. To characterize the knowledge exchange between disciplines, we recognize three aspects of IKF under this framework, namely, broadness, intensity, and homogeneity. We show how to utilize them to uncover different forms of interdisciplinarity, especially between disciplines with the largest volume of IKF. We apply this framework in two use cases, one at the level of disciplines and one at the level of journals, to show how it can offer a more holistic and detailed viewpoint on the interdisciplinarity of scientific entities than aggregated and context-unaware indicators. We further compare our proposed framework, an indicating process, with established indicators and discuss how such information tools on interdisciplinarity can assist science policy practices such as performance-based research funding systems and panel-based peer review processes.

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arXiv2020

Journal article publishing in the social sciences and humanities: a comparison of Web of Science coverage for five European countries

This study compares publication pattern dynamics in the social sciences and humanities in five European countries. Three are Central and Eastern European countries that share a similar cultural and political heritage (the Czech Republic, Slovakia, and Poland). The other two are Flanders (Belgium) and Norway, representing Western Europe and the Nordics, respectively. We analysed 449,409 publications from 2013-2016 and found that, despite persisting differences between the two groups of countries across all disciplines, publication patterns in the Central and Eastern European countries are becoming more similar to those in their Western and Nordic counterparts. Articles from the Central and Eastern European countries are increasingly published in journals indexed in Web of Science and also in journals with the highest citation impacts. There are, however, clear differences between social science and humanities disciplines, which need to be considered in research evaluation and science policy.

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arXiv2016

Measuring the match between evaluators and evaluees: Cognitive distances between panel members and research groups at the journal level

When research groups are evaluated by an expert panel, it is an open question how one can determine the match between panel and research groups. In this paper, we outline two quantitative approaches that determine the cognitive distance between evaluators and evaluees, based on the journals they have published in. We use example data from four research evaluations carried out between 2009 and 2014 at the University of Antwerp. While the barycenter approach is based on a journal map, the similarity-adapted publication vector (SAPV) approach is based on the full journal similarity matrix. Both approaches determine an entity's profile based on the journals in which it has published. Subsequently, we determine the Euclidean distance between the barycenter or SAPV profiles of two entities as an indicator of the cognitive distance between them. Using a bootstrapping approach, we determine confidence intervals for these distances. As such, the present article constitutes a refinement of a previous proposal that operates on the level of Web of Science subject categories.

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arXiv2016

Corrigendum to "Is the expertise of evaluation panels congruent with the research interests of the research groups: a quantitative approach based on barycenters" [Journal of Informetrics 9(4) (2015) 704-721]

In Rahman, Guns, Rousseau, and Engels (2015) we described several approaches to determine the cognitive distance between two units. One of these approaches was based on what we called barycenters in N dimensions. This note corrects this terminology and introduces the more adequate term 'similarity-adapted publication vectors'.

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arXiv2016

A note and a correction on measuring cognitive distance in multiple dimensions

In a previous article (Rahman, Guns, Rousseau, and Engels, 2015) we described several approaches to determine the cognitive distance between two units. One of these approaches was based on what we called barycenters in N dimensions. The present note corrects this terminology and introduces the more adequate term 'similarity-adapted publication vectors'. Furthermore, we correct an error in normalization and explain the importance of scale invariance in determining cognitive distance. We also consider weighted cosine similarity as an alternative approach to determine cognitive (dis)similarity. Overall, we find that the three approaches (distance between barycenters, distance between similarity-adapted publication vectors, and weighted cosine similarity) yield very similar results.

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