An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field
Research highlights
▶ An approach to analyze the thematic evolution of a research field has been proposed. ▶ Strategic diagrams, themes and thematic networks show the conceptual structure. ▶ Thematic areas show the conceptual evolution. ▶ Quantitative and qualitative measures, as h-index, help users to measure the performance of the detected themes and thematic areas.
Introduction
Bibliometrics is usually used for the quantitative research assessment of academic output, and it is starting to be used for practice based research (for more information see Callon et al., 1991, Coulter et al., 1998, Henderson et al., 2009, Ramos-Rodrguez and Ruz-Navarro, 2004, van Raan, 2005a). Concretely, bibliometrics is a set of methods used to study or measure texts and information, especially in big datasets. Many research fields use bibliometric methods to explore the impact of their field, the impact of a set of researchers, or the impact of a particular paper (Henderson et al., 2009, van Raan, 2005a).
In bibliometrics, there are two main procedures: performance analysis and science mapping (Noyons et al., 1999a, van Raan, 2005a). Performance analysis aims at evaluating groups of scientific actors (countries, universities, departments, researchers) and the impact of their activity (Noyons et al., 1999b, van Raan, 2005a) on the basis of bibliographic data. Science mapping aims at displaying the structural and dynamic aspects of scientific research (Börner et al., 2003, Noyons et al., 1999a). A science map is used to represent the cognitive structure of a research field.
Various types of techniques have been developed to build a science map (Small, 2006), the most commonly used being documents co-citation (Small, 1973) and co-word analysis (Callon, Courtial, Turner, & Bauin, 1983). Moreover, different methods have been proposed to address the problem of delimiting a research field, and quantifying and visualizing the detected subfields by means of co-word or co-citation analysis (Börner et al., 2003, Callon et al., 1991, Chen et al., 2010, Coulter et al., 1998, Courtial and Michelet, 1994, Courtial, 1990, Kandylas et al., 2010, Leydesdorff and Rafols, 2009, Rip and Courtial, 1984, Small and Upham, 2009, Small, 1977, Small, 2006, Upham and Small, 2010). The majority of these methods are mainly focused on measuring the performance of the scientific actors and little research has been carried out in order to measure the performance of given research fields in a conceptual way (specific themes or whole thematic areas). A performance analysis of specific themes or whole thematic areas can measure (quantitatively and qualitatively) the relative contribution of these themes and thematic areas to the whole research field, detecting the most prominent, productive, and highest-impact subfields.
The main aim of this paper is to present a general approach to analyze the thematic evolution of a given research field. This approach combines performance analysis and science mapping for detecting and visualizing conceptual subdomains (particular themes or general thematic areas). It also allows us to quantify and visualize the thematic evolution of the research field. To do this, co-word analysis is used in a longitudinal framework (Garfield, 1994). For a better interpretation of the results, strategic diagrams are used in order to categorize the detected themes. Furthermore, thematic areas are used to show conceptual evolution, proposing a visualization approach for graphically showing the thematic evolution of the studied field. Additionally, we develop a performance analysis using different basic bibliometric indicators (the number of published documents, the number of received citations, etc.,) and the h-index (Alonso et al., 2009, Cabrerizo et al., 2010, Hirsch, 2005). As an example, the proposed approach is applied to analyze the thematic evolution of the Fuzzy Sets Theory (FST)1 research field (Zadeh, 1965, Zadeh, 2008) by only considering the documents published in the two most important journals on the topic: Fuzzy Sets and Systems and IEEE Transactions on Fuzzy Systems.
This paper is organized as follows. Section 2 gives a brief overview of the science mapping and longitudinal studies. Section 3 introduces the approach to analyze the evolution of a research field. Section 4 uses the approach in order to analyze the FST research field. Finally, some conclusions are drawn in Section 5.
Section snippets
Science mapping and longitudinal studies
Science mapping or bibliometric mapping is a spatial representation of how disciplines, fields, specialities, and individual papers or authors are related to one another (Small, 1999). It is focused on monitoring a scientific field and delimiting research areas to determine its cognitive structure and its evolution (Noyons, Moed, & van Raan, 1999).
Various types of techniques have been developed to build a science map (Small, 2006), the most commonly used being documents co-citation and co-word
An approach for analyzing a research field
In this section a general approach to carry out a complete analysis of the evolution of a specific research field is shown.
The construction of maps from bibliometric information (Garfield, 1994) is a technique used to show the different themes or topics treated by a scientific field in a given time. Different bibliometric information can be used in order to build a bibliometric map. Depending on the information used, different aspects of the research field can be studied. Co-word analysis and
The research field of fuzzy sets theory
In this section the general approach described above is applied to analyze the research field of Fuzzy Sets Theory (FST) (Zadeh, 1965, Zadeh, 2008) using the publications that have appeared in the most important and prestigious journals of the topic: Fuzzy Sets and Systems and IEEE Transactions on Fuzzy Systems. The first one is the official publication of the International Fuzzy Systems Association (IFSA) and the second one is a publication of the IEEE Computational Intelligence Society for
Concluding remarks
A general approach to analyze and visualize a research field has been proposed. Co-word analysis is the technique used in order to create a bibliometric map. Strategic diagrams and thematic areas are used to study the thematic evolution of a research field. Finally, the performed analysis shows the impact of the research field (including detected themes and thematic areas) by means of quantitative and impact measures such as the h-index.
As an example, this approach has been tested by analyzing
Acknowledgments
This work has been developed with the financing of FEDER funds in FUZZYLING project (TIN2007-61079), FUZZYLING-II project (TIN2010-17876), PETRI project (PET2007-0460), project of Ministry of Public Works (90/07) and Excellence Andalusian Project (TIC5299).
References (56)
- et al.
h-Index: A review focused in its variants, computation and standardization for different scientific fields
Journal of Informetrics
(2009) - et al.
q2-Index: Quantitative and qualitative evaluation based on the number and impact of papers in the hirsch core
Journal of Informetrics
(2010) - et al.
Combining mapping and citation network analysis for a better understanding of the scientific development: The case of the absorptive capacity field
Journal of Informetrics
(2008) - et al.
Community structure of the physical review citation network
Journal of Informetrics
(2010) - et al.
Bibliometric cartography of information retrieval research by using co-word analysis
Information Processing and Management
(2001) - et al.
Co-word-based science maps of chemical engineering. Part i: Representations by direct multidimensional scaling
Research Policy
(1993) Discrete and continuous conceptualizations of science: Implications for knowledge domain visualization
Journal of Informetrics
(2009)Fuzzy sets
Information and Control
(1965)Is there a need for fuzzy logic?
Information Sciences
(2008)- et al.
Analysis of the scientific field of physical chemistry of surfactants with the unified scienctometric model. Fit of relational and activity indicators
Scientometrics
(2005)
The scientific network of surfactants: Structural analysis
Journal of the American Society for Information Science and Technology
Visualizing knowledge domains
Annual Review of Information Science and Technology
Mapping of science by combined co-citation and word analysis. II: Dynamical aspects
Journal of the American Society for Information Science
Comparison of the maps of science
Scientometrics
From translations to problematic networks: An introduction to co-word analysis
Social Science Information
Co-word analysis as a tool for describing the network of interactions between basic and technological research—the case of polymer chemistry
Scientometrics
Searching for intellectual turning points: Progressive knowledge domain visualization
Proceedings of the National Academy of Sciences
The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis
Journal of the American Society for Information Science and Technology
Research group Evaluación de la Ciencia y la Comunicación Cientfica
Software engineering as seen through its research literature: A study in co-word analysis
Journal of the American Society for Information Science
A mathematical model of development in a research field
Scientometrics
A coword analysis of scientometrics
Scientometrics
Scientography: Mapping the tracks of science
Current Contents: Social & Behavioural Sciences
Knowledge discovery through co-word analysis
Library Trends
The quantitative crunch: The impact of bibliometric research quality assessment exercises on academic development at small conferences
Campus-Wide Information Systems
An index to quantify an individuals scientific research out-put
Proceedings of the National Academy of Sciences
Software vulnerability analysis. Ph.D. thesis
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