Browse Our Mathematics and Statistics Journals
Mathematics and statistics journals publish papers on the theory and application of mathematics, statistics, and probability. Most mathematics journals have a broad scope that encompasses most mathematical fields. These commonly include logic and foundations, algebra and number theory, analysis (including differential equations, functional analysis and operator theory), geometry, topology, combinatorics, probability and statistics, numerical analysis and computation theory, mathematical physics, etc.
Mathematics and Statistics
Abstract
Bibliometric counting methods need to be validated against perceived notions of authorship credit allocation, and standardized by rejecting methods with poor fit or questionable ethical implications. Harmonic counting meets these concerns by exhibiting a robust fit to previously published empirical data from medicine, psychology and chemistry, and by complying with three basic ethical criteria for the equitable sharing of authorship credit. Harmonic counting can also incorporate additional byline information about equal contribution, or the elevated status of a corresponding last author. By contrast, several previously proposed counting schemes from the bibliometric literature including arithmetic, geometric and fractional counting, do not fit the empirical data as well and do not consistently meet the ethical criteria. In conclusion, harmonic counting would seem to provide unrivalled accuracy, fairness and flexibility to the long overdue task of standardizing bibliometric allocation of publication and citation credit.
Abstract
In this study the amount of “informal” citations (i.e. those mentioning only author names or their initials instead of the complete references) in comparison to the “formal” (full reference based) citations is analyzed using some pioneers of chemistry and physics as examples. The data reveal that the formal citations often measure only a small fraction of the overall impact of seminal publications. Furthermore, informal citations are mainly given instead of (and not in addition to) formal citations. As a major consequence, the overall impact of pioneering articles and researchers cannot be entirely determined by merely counting the full reference based citations.
Abstract
An individual’s h-index corresponds to the number h of his/her papers that each has at least h citations. When the citation count of an article exceeds h, however, as is the case for the hundreds or even thousands of citations that accompany the most highly cited papers, no additional credit is given (these citations falling outside the so-called “Durfee square”). We propose a new bibliometric index, the “tapered h-index” (h T), that positively enumerates all citations, yet scoring them on an equitable basis with h. The career progression of h T and h are compared for six eminent scientists in contrasting fields. Calculated h T for year 2006 ranged between 44.32 and 72.03, with a corresponding range in h of 26 to 44. We argue that the h T-index is superior to h, both theoretically (it scores all citations), and because it shows smooth increases from year to year as compared with the irregular jumps seen in h. Conversely, the original h-index has the benefit of being conceptually easy to visualise. Qualitatively, the two indices show remarkable similarity (they are closely correlated), such that either can be applied with confidence.
Abstract
Abstract
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.
Abstract
Innovation research builds on the analysis of micro level data describing innovative behaviour of individual firms. One increasingly popular type of data are Literature-based Innovation Output (LBIO) data. These are compiled by screening specialist trade journals for new-product announcements. Notwithstanding the substantial advantages, the eligibility of LBIO data for innovation research remains controversial. In this paper the merits of LBIO data are examined by means of comparative analysis. A newly built LBIO database is systematically compared with the widely used Community Innovation Survey. It shows that both databases identify similar innovators in terms of firm size, distribution across industries and degree of innovativeness: LBIO data can be considered a fully fledged alternative to traditional innovation data, highly eligible for innovation research.
Abstract
This paper examines general characteristics of African science from a quantitative ‘scientometric’ perspective. More specifically, that of research outputs of Africa-based authors published in the scientific literature during the years 1980–2004, either within the international journals representing ‘mainstream’ science, or within national and regional journals reflecting ‘indigenous science’. As for the international journals, the findings derived from Thomson Scientific’s Citation Indexes show that while Africa’s share in worldwide science has steadily declined, the share of international co-publications has increased very significantly, whereas low levels of international citation impact persist. A case study of South African journals reveals the existence of several journals that are not processed for these international databases but nonetheless show a distinctive citation impact on international research communities.
Abstract
The two Journal Citation Reports of the Science Citation Index 2004 and the Social Science Citation Index 2004 were combined in order to analyze and map journals and specialties at the edges and in the overlap between the two databases. For journals which belong to the overlap (e.g., Scientometrics), the merger mainly enriches our insight into the structure which can be obtained from the two databases separately; but in the case of scientific journals which are more marginal in either database, the combination can provide a new perspective on the position and function of these journals (e.g., Environment and Planning B — Planning and Design). The combined database additionally enables us to map citation environments in terms of the various specialties comprehensively. Using the vector-space model, visualizations are provided for specialties that are parts of the overlap (information science, science & technology studies). On the basis of the resulting visualizations, “betweenness” — a measure from social network analysis — is suggested as an indicator for measuring the interdisciplinarity of journals.
Abstract
Bio-pharmaceutical R&D is increasingly an international affair. Research articles published in the peer-reviewed international scientific and technical journals represent quantifiable research outputs of bio-pharmaceutical firms. Large-scale systemic measurements of worldwide trends and sectoral patterns within bio-pharmaceutical science can be gauged from these articles, where coauthored research papers are assumed to reflect research cooperation and associated knowledge flows and exchanges. We focus our attention on the largest science-based multinational enterprises (MNEs), those that produce relatively large quantities of research articles. The study deals with the worldwide output of research articles that are co-produced by corporate researchers during the years 1996–2001. We employ these publications to examine structural factors characterizing research cooperation networks within industry at the level of major geographical regions (North America, Europe, Pacific-Asia), with a breakdown by within-MNE and between-MNE network linkages. The descriptive statistics on publication output and results of network analyses of co-publication linkages not only indicate regional differences, with a central role for US companies in biopharmaceutical research, but also a variety of firm-specific research cooperation networks which enabled us to develop a tentative typology of MNEs in terms of their intra- and interorganizational patterns of research cooperation linkages.
Abstract
This article explores the emergence of knowledge from scientific discoveries and their effects on the structure of scientific communication. Network analysis is applied to understand this emergence institutionally as changes in the journals; semantically as changes in the codification of meaning in terms of words; and cognitively as the new knowledge becomes the emergent foundation of further developments. The discovery of fullerenes in 1985 is analyzed as the scientific discovery that triggered a process which led to research in nanotubes.
