Andrea Scharnhorst

Characteristics and impact of the matthew effect for countries

In this paper newly established characteristics of the so-called Matthew Effect for Countries (MEC) are presented: field-dependency, time-stability, order of magnitude. We find that the MEC is observable in all main scientific fields that were investigated. Over fifteen years the MEC has been relatively stable. The MEC is a redistribution phenomenon at the macro-level of the sciences. Its magnitude is small; the MEC affects only about five percent of the world production of citations. The MEC, however, crucially impacts many nations when their “national loss of citations” amounts to a high percentage of their expected citations. The relationship between the MEC and Mertons Matthew Principle is discussed. It is our hypothesis that the MEC provides an additional approach for the assessment of the scientific performance of nations.

Maps of the academic web in the European Higher Education Area - an exploration of visual web indicators

This paper shows maps of the web presence of the European Higher Education Area (EHEA) on the level of universities using hyperlinks and analyses the topology of the European academic network. Its purpose is to combine methods from Social Network Analysis (SNA) and cybermetric techniques in order to ask for tendencies of integration of the European universities visible in their web presence and the role of different universities in the process of the emergence of an European Research Area. We find as a main result that the European network is set up by the aggregation of well-defined national networks, whereby the German and British networks are dominant. The national networks are connected to each other through outstanding national universities in each country.

Visual conceptualizations and models of science

This Journal of Informetrics special issue aims to improve our understanding of the structure and dynamics of science by reviewing and advancing existing conceptualizations and models of scholarly activity. Several of these conceptualizations and models have visual manifestations supporting the combination and comparison of theories and approaches developed in different disciplines of science. Subsequently, we discuss challenges towards a theoretically grounded and practically useful science of science and provide a brief chronological review of relevant work. Then, we exemplarily present three conceptualizations of science that attempt to provide frameworks for the comparison and combination of existing approaches, theories, laws, and measurements. Finally, we discuss the contributions of and interlinkages among the eight papers included in this issue. Each paper makes a unique contribution towards conceptualizations and models of science and roots this contribution in a review and comparison with existing work.

Self-citations, co-authorships and keywords: A new approach to scientists’ field mobility?

This paper introduces a new approach to detecting scientists’ field mobility by focusing on an author’s self-citation network, and the co-authorships and keywords in self-citing articles. Contrary to much previous literature on self-citations, we will show that author’s self-citation patterns reveal important information on the development and emergence of new research topics over time. More specifically, we will discuss self-citations as a means to detect scientists’ field mobility. We introduce a network based definition of field mobility, using the Optimal Percolation Method (Lambiotte & Ausloos, 2005; 2006). The results of the study can be extended to selfcitation networks of groups of authors and, generally also for other types of networks.

THE APPLICATION OF EVOLUTION MODELS IN SCIENTOMETRICS

According to the connection between field mobility and coupled manpower growth processes in a system of scientific fields a deterministic, stochastic and continuous version of an evolution model is presented. Some simulation results on base of the stochastic model are given in Section 5 and compared with corresponding trend analyses of the deterministic model. Several interesting effects, as delayed growth and temporal disappearance as well as rapid growth and overshooting of a new field, are shown by the simulations.

Nonlinear Stochastic Effects of Substitution--An Evolutionary Approach

Technological innovations have been investigated by means of substitution and diffusion as well as evolution models, each of them dealing with different aspects of the innovation problem. In this paper we follow the well known research traditions on self-organisation models of complex systems. For the first time in the literature we show the existence of a specific niche effect, which may occur in the first stage of establishment of a new technology. Using a stochastic Master equation approach, we obtain analytical expressions for the survival probabilities of a new technology in smaller or larger ensembles. As a main result we demonstrate how a hyperselection situation might be removed in a stochastic picture and thresholds against the prevailing of a new technology in a step-by-step process can be overcome.

Models of Science Dynamics

Models of science dynamics aim to capture the structure and evolution of science. They are developed in an emerging research area in which scholars, scientific institutions and scientific communications become themselves basic objects of research. In order to understand phenomena as diverse as the structure of evolving co-authorship networks or citation diffusion patterns, different models have been developed. They include conceptual models based on historical and ethnographic observations, mathematical descriptions of measurable phenomena, and computational algorithms. Despite its evident importance, the mathematical modeling of science still lacks a unifying framework and a comprehensive research agenda.This book aims to fill this gap, reviewing and describing major threads in the mathematical modeling of science dynamics for a wider academic and professional audience. The model classes presented here cover stochastic and statistical models, game-theoretic approaches, agent-based simulations, population-dynamics models, and complex network models. The book starts with a foundational chapter that defines and operationalizes terminology used in the study of science, and a review chapter that discusses the history of mathematical approaches to modeling science from an algorithmic-historiography perspective. It concludes with a survey of future challenges for science modeling and discusses their relevance for science policy and science policy studies.

The matthew index—Concentration patterns and Matthew core journals

In this paper we extend our studies to the micro-structure of the Matthew effect for countries (MEC). The MEC allows the ranking of countries by their Matthew Index. The rank distribution of countries, observable only at a macro-level, has its roots in re-distribution processes of citations in every journal of the database. These re-distributed citations we call Matthew citations. Data for 44 countries and 2712 journals (based on theScience Citation Index) are analyzed. The strength of the contribution of the individual journals to the MEC (their number of Matthew citations) is skewly distributed. Due to this high concentration of the MEC we are able to define a new type of journal the Matthew core journal: 145 Matthew core journals account for 50% of the MEC. These journals carry a high potential of gaining a surplus of citations over what is expected and the risk of losing a high number of citations as well.

Scientometrics and information retrieval: weak-links revitalized

This special issue brings together eight papers from experts of communities which often have been perceived as different once: bibliometrics, scientometrics and informetrics on the one side and information retrieval on the other. The idea of this special issue started at the workshop “Combining Bibliometrics and Information Retrieval” held at the 14th International Conference of Scientometrics and Informetrics, Vienna, July 14–19, 2013. Our motivation as guest editors started from the observation that main discourses in both fields are different, that communities are only partly overlapping and from the belief that a knowledge transfer would be profitable for both sides.

Not Another Case Study A Middle-Range Interrogation of Ethnographic Case Studies in the Exploration of E-science

This article addresses the need to problematize “cases” in science and technology studies (STS) work, as a middle-range theory issue. The focus is not on any one case study per se, but on why case studies exist and endure in STS. Case studies are part of a specific problematization in the field. We therefore explore relations between motivation for the use of cases (especially ethnographic ones), their constitution, and ways they can be invoked to make particular kinds of arguments in STS. We set out to examine the case as an object that links together research practices, intellectual debates, and programmatic concerns in our own work. Based on our experiences and on this reflection on the links between cases and questions in STS, we propose a number of casemaking strategies that shift and enrich the deployment of ethnographic cases as an epistemic tool in STS.