Power laws in citation distributions: evidence from Scopus

Global trends in tumor-associated neutrophil research: a bibliometric and visual analysis

Background

Tumor-associated neutrophils (TANs) play crucial roles in tumor progression, immune response modulation, and the therapeutic outcomes. Despite significant advancements in TAN research, a comprehensive bibliometric analysis that objectively presents the current status and trends in this field is lacking. This study aims to fill this gap by visually analyzing global trends in TANs research using bibliometric and knowledge mapping techniques.

Methods

We retrieved articles and reviews related to TANs from the Web of Science core collection database, spanning the period from 2012 to2024. The data was analyzed using bibliometric tools such as Excel 365, CiteSpace, VOSviewer, and Bibliometrix (R-Tool of R-Studio) to identify key trends, influential countries and institutions, collaborative networks. and citation patterns.

Results

A total of 6l5 publications were included in the bibliometric analysis, showing a significant upward trend in TANs research over the last two decades. The United States and China emerged as the leading contributors with the highest number of publications and citations. The journal with the most publications in this field is Frontiers in Immunology, Prominent authors such as Fridlender ZG was identified as the key contributor, with his works frequently cited. The analysis highlighted major research themes. including the role of TANs in tumor microenvironment modulation, their dual functions in tumor promotion and suppression, and the exploration of TANs-targeted therapies, Emerging research hotspots include studies on TANs plasticity and their interactions with other immune cells.

Conclusion

This study is the first to employ bibliometric methods to visualize trends and frontiers in TANs research. The findings provide valuable insights into the evolution of the field, highlighting critical areas for future investigation and potential collaborative opportunities. This comprehensive analysis serves as a crucial resource for researchers and practitioners aiming to advance TAN research and its application in cancer therapy.

Weighted-ensemble network simulations of the susceptible-infected-susceptible model of epidemics

The presence of erratic or unstable paths in standard kinetic Monte Carlo simulations significantly undermines the accurate simulation and sampling of transition pathways. While typically reliable methods, such as the Gillespie algorithm, are employed to simulate such paths, they encounter challenges in efficiently identifying rare events due to their sequential nature and reliance on exact Monte Carlo sampling. In contrast, the weighted-ensemble method effectively samples rare events and accelerates the exploration of complex reaction pathways by distributing computational resources among multiple replicas, where each replica is assigned a weight reflecting its importance, and evolves independently from the others. Here, we implement the highly efficient and robust weighted-ensemble method to model susceptible-infected-susceptible dynamics on large heterogeneous population networks, and explore the interplay between stochasticity and contact heterogeneity, which ultimately gives rise to disease clearance. Studying a wide variety of networks characterized by fat-tailed asymmetric degree distributions, we are able to compute the mean time to extinction and quasistationary distribution around it in previously inaccessible parameter regimes.

A career in numbers: A citation network analysis of the work of RP Millar and his contribution to GnRH research

Here, we reflect on the long career in neuroendocrinology of a single, highly productive scientist ('Bob' Millar), by analysing his oeuvre of published papers through the lens of citation metrics. We use citation network analysis in a novel manner to identify the specific topics to which his papers have made a particular contribution, allowing us to compare the citations of his papers with those of contemporary papers on the same topic, rather than on the same broad field as generally used to normalise citations. It appears that citation rates are highest for topics on which Bob has published a relatively large number of papers that have become core to a tightly-knit community of authors that cite each other. This analysis shows that an author's impact depends on the existence of a receptive community that is alert to the potential utility of papers from that author, and which uses, amplifies, extends and qualifies the contents of their papers-activities that entail reciprocal citation between authors. The obvious conclusion is that a scientist's impact depends on the use that his or her contemporaries make of his or her contributions, rather than on the contributions in themselves.

Clinical Impact of "Real World Data" and Blockchain on Public Health: A Scoping Review

The digitisation of healthcare has allowed a significant rethinking of the previous clinical protocols, improving their interoperability through substantial standardisation. These technological advances have ensured that data are comparable, as they are obtained from 'reliable' and certified processes; however, there are billions of data that are neither structured nor quality-controlled. They are collectively referred to as 'Real World Data' (RWD). Blockchain (BC) is a procedure with specific characteristics and algorithms that ensure that the stored data cannot be tampered with. Nowadays, there is an increasing need to rethink blockchain in a one-health vision, making it more than just a 'repository' of data and information, but rather an active player in the process of data sharing. In this landscape, several scholars have analysed the potential benefits of BC in healthcare, focusing on the sharing and safety of clinical data and its contact tracing applications. There is limited research on this matter; moreover, there is a strategic interest in managing RWD in a reliable and comparable way, despite the lack of knowledge on this topic. Our work aims to analyse systematically the most impacting literature, highlighting the main aspects of BC within the context of the new digital healthcare, and speculating on the unexpressed potential of RWD.

Measuring the variability of local characteristics in complex networks: Empirical and analytical analysis

We examine the dynamics for the average degree of a node's neighbors in complex networks. It is a Markov stochastic process, and at each moment of time, this quantity takes on its values in accordance with some probability distribution. We are interested in some characteristics of this distribution: its expectation and its variance, as well as its coefficient of variation. First, we look at several real communities to understand how these values change over time in social networks. The empirical analysis of the behavior of these quantities for real networks shows that the coefficient of variation remains at high level as the network grows. This means that the standard deviation and the mean degree of the neighbors are comparable. Then, we examine the evolution of these three quantities over time for networks obtained as simulations of one of the well-known varieties of the Barabási-Albert model, the growth model with nonlinear preferential attachment (NPA) and a fixed number of attached links at each iteration. We analytically show that the coefficient of variation for the average degree of a node's neighbors tends to zero in such networks (albeit very slowly). Thus, we establish that the behavior of the average degree of neighbors in Barabási-Albert networks differs from its behavior in real networks. In this regard, we propose a model based on the NPA mechanism with the rule of random number of edges added at each iteration in which the dynamics of the average degree of neighbors is comparable to its dynamics in real networks.

Understanding equity sensitivity through the lens of personality: a review of associations and underlying nature

Purpose

This study aims to clarify the ambiguous nature of equity sensitivity and understand the associations between equity perceptions and the personality domain in organizational behaviour.

Design/methodology/approach

The study reviews 56 articles that rendered associations between different HEXACO personality domains and equity sensitivity and proposed a possibility of equity sensitivity being a situation-activated trait.

Findings

The domains of Honesty-humility, Conscientiousness and Agreeableness are predominantly associated with equity sensitivity. The domain of Emotionality is also associated but not as significant as the aforementioned domains. Unexpectedly, Extraversion, the domain of social interactions, and Openness to experience showed little to no associations. The transient nature of equity sensitivity has been proposed that postulates that such nature might help predict an individual’s personality characteristics in a given context.

Originality/value

This review is one of the first, to the best of the authors’ knowledge, to describe the associations between equity sensitivity and the HEXACO personality domains. Additionally, the situational nature of equity sensitivity and relationship with the personality traits is proposed.

Mapping the quantity, quality and structural indicators of Asian (48 countries and 3 territories) research productivity on cloud computing

Purpose

The purpose of this study was to map the quantity (frequency), quality (impact) and structural indicators (correlations) of research produced on cloud computing in 48 countries and 3 territories in the Asia continent.

Design/methodology/approach

To achieve the objectives of the study and scientifically map the indicators, data were extracted from the Scopus database. The extracted bibliographic data was first cleaned properly using Endnote and then analyzed using Biblioshiny and VosViewer application software. In the software, calculations include citations count; h, g and m indexes; Bradford's and Lotka's laws; and other scientific mappings.

Findings

Results of the study indicate that China remained the most productive, impactful and collaborative country in Asia. All the top 20 impactful authors were also from China. The other most researched areas associated with cloud computing were revealed to be mobile cloud computing and data security in clouds. The most prominent journal currently publishing research studies on cloud computing was “Advances in Intelligent Systems and Computing.”

Originality/value

The study is the first of its kind which identified the quantity (frequencies), quality (impact) and structural indicators (correlations) of Asian (48 countries and 3 territories) research productivity on cloud computing. The results are of great importance for researchers and countries interested in further exploring, publishing and increasing cross country collaborations related to the phenomenon of cloud computing.

The human side of humanitarian supply chains: a research agenda and systematization framework

Humanitarian operations are increasingly receiving attention due to the numerous recent disasters and crises caused by both natural and man-made events, from mass human exodus to pandemics such as COVID-19. The successful management of humanitarian supply chains requires the effective use of human resource practices, which in turn requires strong leadership in the so-called 'soft side' of management. This study aims to investigate the current status of research on the human aspects of humanitarian supply chains. Through a systematic and comprehensive literature review, encompassing an original codification and in-depth analysis of journal articles, this work provides a research agenda and a number of lessons concerning human resource management (HRM) in humanitarian operations. The main findings reveal that: (i) HRM impacts the ability of humanitarian organizations to adequately prevent, prepare for and respond to disasters; (ii) training programs for aid personnel are a vital aspect of humanitarian responsiveness; (iii) humanitarian operations require a workforce with a variety of soft and hard skills; (iv) lack of trained staff is one of the main challenges in this field; and (v) building relationships and strengthening networks can enlarge the human resource pool available. Therefore, the findings of this study and its proposed research agenda have implications for both theory and practice. In terms of theory, this work provides seven recommendations, representing opportunities for scholars to advance this body of knowledge. For humanitarian practitioners, this paper offers insightful lessons to guide them in the management of human resources in humanitarian operations.

A Bayesian hurdle quantile regression model for citation analysis with mass points at lower values

Quantile regression presents a complete picture of the effects on the location, scale, and shape of the dependent variable at all points, not just the mean. We focus on two challenges for citation count analysis by quantile regression: discontinuity and substantial mass points at lower counts. A Bayesian hurdle quantile regression model for count data with a substantial mass point at zero was proposed by King and Song (2019). It uses quantile regression for modeling the nonzero data and logistic regression for modeling the probability of zeros versus nonzeros. We show that substantial mass points for low citation counts will almost certainly also affect parameter estimation in the quantile regression part of the model, similar to a mass point at zero. We update the King and Song model by shifting the hurdle point past the main mass points. This model delivers more accurate quantile regression for moderately to highly cited articles, especially at quantiles corresponding to values just beyond the mass points, and enables estimates of the extent to which factors influence the chances that an article will be low cited. To illustrate the potential of this method, it is applied to simulated citation counts and data from Scopus.

Differences in Citation Patterns across Areas, Article Types and Age Groups of Researchers

The evaluation of research proposals and academic careers is subject to indicators of scientific productivity. Citations are critical signs of impact for researchers, and many indicators are based on these data. The literature shows that there are differences in citation patterns between areas. The scope and depth that these differences may have to motivate the extension of these studies considering types of articles and age groups of researchers. In this work, we conducted an exploratory study to elucidate what evidence there is about the existence of these differences in citation patterns. To perform this study, we collected historical data from Scopus. Analyzing these data, we evaluate if there are measurable differences in citation patterns. This study shows that there are evident differences in citation patterns between areas, types of publications, and age groups of researchers that may be relevant when carrying out researchers’ academic evaluation.

Blockchain technology in the smart city: a bibliometric review

Blockchain can function as a foundational technology with numerous applications in smart cities. The objective of this paper is twofold. First, it provides a detailed overview of the extant literature on blockchain applications in smart cities; second, it reveals the trends and suggests future research directions for scholars who wish to contribute to this rapidly growing field. We conducted a bibliometric review using a keyword co-occurrence network and article co-citation analysis. The analysis includes the assessment of 148 articles published between 2016 and 2020 in 76 academic journals. The review results demonstrate that the number of articles devoted to the study of blockchain applications and smart cities has increased exponentially in recent years. More importantly, the research identifies some of the most influential studies in this area. The paper discusses trends and highlights the challenges related to the deployment of blockchain in smart cities. To the authors’ best knowledge, this represents the first study to review the literature from leading journals on blockchain applications in smart cities using bibliometric techniques.

Winter Sports Resorts and Natural Environment—Systematic Literature Review Presenting Interactions between Them

The systematic literature review method was adopted to analyze the content of papers published since 2001 that focused on interactions between winter sports resort operations and the natural environment. A total of 86 papers published in journals indexed in SCOPUS data base were analyzed. Three main groups of topics presented in analyzed papers were found: the environmental impact of winter sports resorts, the management of environmental impacts and sustainable development of winter sports resorts, and finally the impact of climate change on winter sports resort operations. The biggest number of publications were devoted to the latter topic, and interest in conducting research within this area has apparently grown during the last two decades. However, most conclusions reached by the authors of numerous studies are site-specific and difficult to extend to other resorts/destinations. Additionally, the conclusions presented in many papers are contrary to the results achieved in other publications. Several gaps in our contemporary scientific knowledge and directions of future research are suggested in addition to the abovementioned results of the analysis conducted in the presented paper as the final conclusion of the research.

A machine learning toolkit for genetic engineering attribution to facilitate biosecurity

The promise of biotechnology is tempered by its potential for accidental or deliberate misuse. Reliably identifying telltale signatures characteristic to different genetic designers, termed 'genetic engineering attribution', would deter misuse, yet is still considered unsolved. Here, we show that recurrent neural networks trained on DNA motifs and basic phenotype data can reach 70% attribution accuracy in distinguishing between over 1,300 labs. To make these models usable in practice, we introduce a framework for weighing predictions against other investigative evidence using calibration, and bring our model to within 1.6% of perfect calibration. Additionally, we demonstrate that simple models can accurately predict both the nation-state-of-origin and ancestor labs, forming the foundation of an integrated attribution toolkit which should promote responsible innovation and international security alike.

Re-evaluating Phoneme Frequencies

Causal processes can give rise to distinctive distributions in the linguistic variables that they affect. Consequently, a secure understanding of a variable's distribution can hold a key to understanding the forces that have causally shaped it. A storied distribution in linguistics has been Zipf's law, a kind of power law. In the wake of a major debate in the sciences around power-law hypotheses and the unreliability of earlier methods of evaluating them, here we re-evaluate the distributions claimed to characterize phoneme frequencies. We infer the fit of power laws and three alternative distributions to 166 Australian languages, using a maximum likelihood framework. We find evidence supporting earlier results, but also nuancing them and increasing our understanding of them. Most notably, phonemic inventories appear to have a Zipfian-like frequency structure among their most-frequent members (though perhaps also a lognormal structure) but a geometric (or exponential) structure among the least-frequent. We compare these new insights the kinds of causal processes that affect the evolution of phonemic inventories over time, and identify a potential account for why, despite there being an important role for phonetic substance in phonemic change, we could still expect inventories with highly diverse phonetic content to share similar distributions of phoneme frequencies. We conclude with priorities for future work in this promising program of research.

An Extensive Knowledge Mapping Review of Measurement and Validity in Language Assessment and SLA Research

This study set out to investigate intellectual domains as well as the use of measurement and validation methods in language assessment research and second language acquisition (SLA) published in English in peer-reviewed journals. Using Scopus, we created two datasets: (i) a dataset of core journals consisting of 1,561 articles published in four language assessment journals, and (ii) a dataset of general journals consisting of 3,175 articles on language assessment published in the top journals of SLA and applied linguistics. We applied document co-citation analysis to detect thematically distinct research clusters. Next, we coded citing papers in each cluster based on an analytical framework for measurement and validation. We found that the focus of the core journals was more exclusively on reading and listening comprehension assessment (primary), facets of speaking and writing performance such as raters and validation (secondary), as well as feedback, corpus linguistics, and washback (tertiary). By contrast, the primary focus of assessment research in the general journals was on vocabulary, oral proficiency, essay writing, grammar, and reading. The secondary focus was on affective schemata, awareness, memory, language proficiency, explicit vs. implicit language knowledge, language or semantic awareness, and semantic complexity. With the exception of language proficiency, this second area of focus was absent in the core journals. It was further found that the majority of citing publications in the two datasets did not carry out inference-based validation on their instruments before using them. More research is needed to determine what motivates authors to select and investigate a topic, how thoroughly they cite past research, and what internal (within a field) and external (between fields) factors lead to the sustainability of a Research Topic in language assessment.

Digitally-enabled sustainable supply chains in the 21st century: A review and a research agenda

While the potential benefits of integrating digital technologies and supply chain management have been widely reported, less is known concerning the current state-of-the-art literature on big data-driven sustainable supply chains. Therefore, this study aims to systematise published studies which address the implications of big data for sustainable supply chain management. Through a systematic literature review, this work makes three significant contributions: (a) it provides an overview of extant literature on this topic in recent years; (b) it proposes seven gaps in the literature in order to foster future investigations on big data-driven sustainable supply chains; (c) it offers four lessons for business practitioners aiming to use big data for sustainable supply chain practices. These lessons suggest that: developing big data analytics capability has to become a business priority in order to effectively build competitive sustainable supply chains; big data has benefits for each of the dimensions of the triple-bottom-line in supply chains; the implementation of big data for sustainability in supply chains presents some challenges for firms; the development of complementary organizational capabilities is needed to overcome challenges and facilitate the benefits of big data technology for sustainable supply chain management.

Three dimensions of scientific impact

The growing popularity of bibliometric indexes (whose most famous example is the h index by J. E. Hirsch [J. E. Hirsch, Proc. Natl. Acad. Sci. U.S.A. 102, 16569-16572 (2005)]) is opposed by those claiming that one's scientific impact cannot be reduced to a single number. Some even believe that our complex reality fails to submit to any quantitative description. We argue that neither of the two controversial extremes is true. By assuming that some citations are distributed according to the rich get richer rule (success breeds success, preferential attachment) while some others are assigned totally at random (all in all, a paper needs a bibliography), we have crafted a model that accurately summarizes citation records with merely three easily interpretable parameters: productivity, total impact, and how lucky an author has been so far.

Financial Technology: Review of Trends, Approaches and Management

Technological innovation and digitization have posed a challenge to the financial sector globally. Fintech is the term used to designate the application of new technologies to financial services. The aim of the study is to analyse this research subject worldwide during the period 1975–2019. To this end, bibliometric techniques were applied to 2012 articles, obtaining findings of the productivity of scientific research, of the main thematic axes and their evolution. Scientific activity increased, mainly in the past decade, with 45% of publications. The main thematic areas were Business, Management and Accounting, Engineering, Social Sciences and Computer Science. Seven research lines were identified, aimed at analysing the aspects financial, economic, technology transfer, investment, innovation, partnerships and institutions and commercial. Future research lines should develop analyses on banking, financial services trade, territorial development, legal, management, research methodologies and the sustainability of financial technologies. It was verified that there is a growing and dynamic interest in scientific activity on financial technologies at an international level. The findings obtained are a complement to the knowledge of financial technologies and allow the relationship between science and technology to be established, and to inform the decision-making process.

Neutral syndrome

Neutral models of evolution assume the absence of natural selection. Formerly confined to ecology and evolutionary biology, neutral models are spreading. In recent years they've been applied to explaining the diversity of baby names, scientific citations, cryptocurrencies, pot decorations, literary lexica, tumour variants and much more besides. Here, we survey important neutral models and highlight their similarities. We investigate the most widely used tests of neutrality, show that they are weak and suggest more powerful methods. We conclude by discussing the role of neutral models in the explanation of diversity. We suggest that the ability of neutral models to fit low-information distributions should not be taken as evidence for the absence of selection. Nevertheless, many studies, in increasingly diverse fields, make just such claims. We call this tendency 'neutral syndrome'.

Science through Wikipedia: A novel representation of open knowledge through co-citation networks

This study provides an overview of science from the Wikipedia perspective. A methodology has been established for the analysis of how Wikipedia editors regard science through their references to scientific papers. The method of co-citation has been adapted to this context in order to generate Pathfinder networks (PFNET) that highlight the most relevant scientific journals and categories, and their interactions in order to find out how scientific literature is consumed through this open encyclopaedia. In addition to this, their obsolescence has been studied through Price index. A total of 1 433 457 references available at Altmetric.com have been initially taken into account. After pre-processing and linking them to the data from Elsevier's CiteScore Metrics the sample was reduced to 847 512 references made by 193 802 Wikipedia articles to 598 746 scientific articles belonging to 14 149 journals indexed in Scopus. As highlighted results we found a significative presence of “Medicine” and “Biochemistry, Genetics and Molecular Biology” papers and that the most important journals are multidisciplinary in nature, suggesting also that high-impact factor journals were more likely to be cited. Furthermore, only 13.44% of Wikipedia citations are to Open Access journals.

On entropy research analysis: cross-disciplinary knowledge transfer

Our aim is to illustrate how the thermodynamics-based concept of entropy has spread across different areas of knowledge by analyzing the distribution of papers, citations and the use of words related to entropy in the predefined Scopus categories. To achieve this, we analyze the Scopus papers database related to entropy research during the last 20 years, collecting 750 K research papers which directly contain or mention the word entropy. First, some well-recognized works which introduced novel entropy-related definitions are monitored. Then we compare the hierarchical structure which emerges for the different cases of association, which can be in terms of citations among papers, classification of papers in categories or key words in abstracts and titles. Our study allowed us to evaluate, to some extent, the utility and versatility of concepts such as entropy to permeate in different areas of science. Furthermore, the use of specific terms (key words) in titles and abstracts provided a useful way to account for the interaction between areas in the category research space.

“In sickness and in health, in poverty and in wealth?”

Purpose

“Economic crises” and “corporate social responsibility (CSR) initiatives” are two issues that dominate the modern business agenda. Although related, these issues have been analysed separately, and so a significant gap is perpetuated between the two. What are the effects of economic crises on CSR initiatives? Can organisational social initiatives withstand economic crises? The purpose of this paper is to answer these questions.

Design/methodology/approach

An integrative literature review was conducted, considering: the economic and geographical context in which the research was conducted; the focus of each piece of research; the adopted research methods; organisational theories of analytical support; the sectors analysed; and the effects of economic crises on CSR initiatives and environmental management.

Findings

Some of the findings were as follows: most of the studies analysed reported that CSR helps companies to cope with economic crises by increasing the efficiency of investments and establishing better relations with stakeholders and markets; environmental practices are related to negative environmental performance in periods of economic crises; and CSR relates positively to financial performance in periods of economic crises.

Originality/value

This is one of the first integrative literature reviews to investigate what happens to the relationship between businesses and sustainable change management in periods of crises. This paper also offers a future research agenda for the issue, with 12 questions still unanswered by the latest research.

Power-law citation distributions are not scale-free

We analyze time evolution of statistical distributions of citations to scientific papers published in the same year. While these distributions seem to follow the power-law dependence we find that they are nonstationary and the exponent of the power-law fit decreases with time and does not come to saturation. We attribute the nonstationarity of citation distributions to different longevity of the low-cited and highly cited papers. By measuring citation trajectories of papers we found that citation careers of the low-cited papers come to saturation after 10-15 years while those of the highly cited papers continue to increase indefinitely: The papers that exceed some citation threshold become runaways. Thus, we show that although citation distribution can look as a power-law dependence, it is not scale free and there is a hidden dynamic scale associated with the onset of runaways. We compare our measurements to our recently developed model of citation dynamics based on copying-redirection-triadic closure and find explanations to our empirical observations.

Science and Facebook: The same popularity law!

The distribution of scientific citations for publications selected with different rules (author, topic, institution, country, journal, etc…) collapse on a single curve if one plots the citations relative to their mean value. We find that the distribution of “shares” for the Facebook posts rescale in the same manner to the very same curve with scientific citations. This finding suggests that citations are subjected to the same growth mechanism with Facebook popularity measures, being influenced by a statistically similar social environment and selection mechanism. In a simple master-equation approach the exponential growth of the number of publications and a preferential selection mechanism leads to a Tsallis-Pareto distribution offering an excellent description for the observed statistics. Based on our model and on the data derived from PubMed we predict that according to the present trend the average citations per scientific publications exponentially relaxes to about 4.

A Unified Framework for Complex Networks with Degree Trichotomy Based on Markov Chains

This paper establishes a Markov chain model as a unified framework for describing the evolution processes in complex networks. The unique feature of the proposed model is its capability in addressing the formation mechanism that can reflect the "trichotomy" observed in degree distributions, based on which closed-form solutions can be derived. Important special cases of the proposed unified framework are those classical models, including Poisson, Exponential, Power-law distributed networks. Both simulation and experimental results demonstrate a good match of the proposed model with real datasets, showing its superiority over the classical models. Implications of the model to various applications including citation analysis, online social networks, and vehicular networks design, are also discussed in the paper.

The emergence and evolution of the research fronts in HIV/AIDS research

In this paper, we have identified and analyzed the emergence, structure and dynamics of the paradigmatic research fronts that established the fundamentals of the biomedical knowledge on HIV/AIDS. A search of papers with the identifiers "HIV/AIDS", "Human Immunodeficiency Virus", "HIV-1" and "Acquired Immunodeficiency Syndrome" in the Web of Science (Thomson Reuters), was carried out. A citation network of those papers was constructed. Then, a sub-network of the papers with the highest number of inter-citations (with a minimal in-degree of 28) was selected to perform a combination of network clustering and text mining to identify the paradigmatic research fronts and analyze their dynamics. Thirteen research fronts were identified in this sub-network. The biggest and oldest front is related to the clinical knowledge on the disease in the patient. Nine of the fronts are related to the study of specific molecular structures and mechanisms and two of these fronts are related to the development of drugs. The rest of the fronts are related to the study of the disease at the cellular level. Interestingly, the emergence of these fronts occurred in successive "waves" over the time which suggest a transition in the paradigmatic focus. The emergence and evolution of the biomedical fronts in HIV/AIDS research is explained not just by the partition of the problem in elements and interactions leading to increasingly specialized communities, but also by changes in the technological context of this health problem and the dramatic changes in the epidemiological reality of HIV/AIDS that occurred between 1993 and 1995.

Science Mapping: A Systematic Review of the Literature

Purpose

We present a systematic review of the literature concerning major aspects of science mapping to serve two primary purposes: First, to demonstrate the use of a science mapping approach to perform the review so that researchers may apply the procedure to the review of a scientific domain of their own interest, and second, to identify major areas of research activities concerning science mapping, intellectual milestones in the development of key specialties, evolutionary stages of major specialties involved, and the dynamics of transitions from one specialty to another.

Design/methodology/approach

We first introduce a theoretical framework of the evolution of a scientific specialty. Then we demonstrate a generic search strategy that can be used to construct a representative dataset of bibliographic records of a domain of research. Next, progressively synthesized co-citation networks are constructed and visualized to aid visual analytic studies of the domain’s structural and dynamic patterns and trends. Finally, trajectories of citations made by particular types of authors and articles are presented to illustrate the predictive potential of the analytic approach.

Findings

The evolution of the science mapping research involves the development of a number of interrelated specialties. Four major specialties are discussed in detail in terms of four evolutionary stages: conceptualization, tool construction, application, and codification. Underlying connections between major specialties are also explored. The predictive analysis demonstrates citations trajectories of potentially transformative contributions.

Research limitations

The systematic review is primarily guided by citation patterns in the dataset retrieved from the literature. The scope of the data is limited by the source of the retrieval, i.e. the Web of Science, and the composite query used. An iterative query refinement is possible if one would like to improve the data quality, although the current approach serves our purpose adequately. More in-depth analyses of each specialty would be more revealing by incorporating additional methods such as citation context analysis and studies of other aspects of scholarly publications.

Practical implications

The underlying analytic process of science mapping serves many practical needs, notably bibliometric mapping, knowledge domain visualization, and visualization of scientific literature. In order to master such a complex process of science mapping, researchers often need to develop a diverse set of skills and knowledge that may span multiple disciplines. The approach demonstrated in this article provides a generic method for conducting a systematic review.

Originality/value

Incorporating the evolutionary stages of a specialty into the visual analytic study of a research domain is innovative. It provides a systematic methodology for researchers to achieve a good understanding of how scientific fields evolve, to recognize potentially insightful patterns from visually encoded signs, and to synthesize various information so as to capture the state of the art of the domain.