Quantifying the interdisciplinarity of scientific journals and fields

There is an overall perception of increased interdisciplinarity in science, but this is difficult to confirm quantitatively owing to the lack of adequate methods to evaluate subjective phenomena. This is no different from the difficulties in establishing quantitative relationships in human and social sciences. In this paper we quantified the interdisciplinarity of scientific journals and science fields by using an entropy measurement based on the diversity of the subject categories of journals citing a specific journal. The methodology consisted in building citation networks using the Journal Citation Reports database, in which the nodes were journals and edges were established based on citations among journals. The overall network for the 11-year period (1999-2009) studied was small-world and scale free with regard to the in-strength. Upon visualizing the network topology an overall structure of the various science fields could be inferred, especially their interconnections. We confirmed quantitatively that science fields are becoming increasingly interdisciplinary, with the degree of interdisplinarity (i.e. entropy) correlating strongly with the in-strength of journals and with the impact factor.Comment: 23 pages, 6 figure

Social and Natural Sciences Differ in Their Research Strategies, Adapted to Work for Different Knowledge Landscapes

Do different fields of knowledge require different research strategies? A numerical model exploring different virtual knowledge landscapes, revealed two diverging optimal search strategies. Trend following is maximized when the popularity of new discoveries determine the number of individuals researching it. This strategy works best when many researchers explore few large areas of knowledge. In contrast, individuals or small groups of researchers are better in discovering small bits of information in dispersed knowledge landscapes. Bibliometric data of scientific publications showed a continuous bipolar distribution of these strategies, ranging from natural sciences, with highly cited publications in journals containing a large number of articles, to the social sciences, with rarely cited publications in many journals containing a small number of articles. The natural sciences seem to adapt their research strategies to landscapes with large concentrated knowledge clusters, whereas social sciences seem to have adapted to search in landscapes with many small isolated knowledge clusters. Similar bipolar distributions were obtained when comparing levels of insularity estimated by indicators of international collaboration and levels of country-self citations: researchers in academic areas with many journals such as social sciences, arts and humanities, were the most isolated, and that was true in different regions of the world. The work shows that quantitative measures estimating differences between academic disciplines improve our understanding of different research strategies, eventually helping interdisciplinary research and may be also help improve science policies worldwide.Comment: Formerly called: Simulations suggest that social and natural sciences differ in their research strategies adapted to work for different knowledge landscape

Interdisciplinarity metric based on the co-citation network

Quantifying the interdisciplinarity of a research is a relevant problem in the evaluative bibliometrics. The concept of interdisciplinarity is ambiguous and multidimensional. Thus, different measures of interdisciplinarity have been propose in the literature. However, few studies have proposed interdisciplinary metrics without previously defining classification sets, and no one use the co-citation network for this purpose. In this study we propose an interdisciplinary metric based on the co-citation network. This is a way to define the publication's field without resorting to pre-defined classification sets. We present a characterization of a publication's field and then we use this definition to propose a new metric of the interdisciplinarity degree for publications (papers) and journals as units of analysis. The proposed measure has an aggregative property that makes it scalable from a paper individually to a set of them (journal) without more than adding the numerators and denominators in the proportions that define this new indicator. Moreover, the aggregated value of two or more units is strictly among all the individual values.Comment: 9 pages, 2 figures, 1 tabl

Distribution of Citations in one Volume of a Journal

Citations to published scientific articles are regularly collected and processed, bringing about the impact factor and a large number of other bibliometric indicators. We interpret the set of citations collected during fixed period as a characteristic statistical distribution of citations, argue about its properties and conjecture what statistical measures represent reliably such distributions. In that way we try to contribute to determining precisely the scope and level of suitability of impact factor if accompanied with a small set of additional indicators, all derived solely from the distribution function

Complex network analysis of CA3 transcriptome reveals pathogenic and compensatory pathways in refractory temporal lobe epilepsy

We previously described - studying transcriptional signatures of hippocampal CA3 explants - that febrile (FS) and afebrile (NFS) forms of refractory mesial temporal lobe epilepsy constitute two distinct genomic phenotypes. That network analysis was based on a limited number (hundreds) of differentially expressed genes (DE networks) among a large set of valid transcripts (close to two tens of thousands). Here we developed a methodology for complex network visualization (3D) and analysis that allows the categorization of network nodes according to distinct hierarchical levels of gene-gene connections (node degree) and of interconnection between node neighbors (concentric node degree). Hubs are highly connected nodes, VIPs have low node degree but connect only with hubs, and high-hubs have VIP status and high overall number of connections. Studying the whole set of CA3 valid transcripts we: i) obtained complete transcriptional networks (CO) for FS and NFS phenotypic groups; ii) examined how CO and DE networks are related; iii) characterized genomic and molecular mechanisms underlying FS and NFS phenotypes, identifying potential novel targets for therapeutic interventions. We found that: i) DE hubs and VIPs are evenly distributed inside the CO networks; ii) most DE hubs and VIPs are related to synaptic transmission and neuronal excitability whereas most CO hubs, VIPs and high hubs are related to neuronal differentiation, homeostasis and neuroprotection, indicating compensatory mechanisms. Complex network visualization and analysis is a useful tool for systems biology approaches to multifactorial diseases. Network centrality observed for hubs, VIPs and high hubs of CO networks, is consistent with the network disease model, where a group of nodes whose perturbation leads to a disease phenotype occupies a central position in the network.Conceivably, the chance for exerting therapeutic effects through the modulation of particular genes will be higher if these genes are highly interconnected in transcriptional networks.FAPESP (09/53443-1, 05/56446-0, 05/00587-5, 11/50761-2)CNPq (305635/2009-3, 301303/06-1, 573583/2008-0

A Review of Theory and Practice in Scientometrics

Scientometrics is the study of the quantitative aspects of the process of science as a communication system. It is centrally, but not only, concerned with the analysis of citations in the academic literature. In recent years it has come to play a major role in the measurement and evaluation of research performance. In this review we consider: the historical development of scientometrics, sources of citation data, citation metrics and the “laws" of scientometrics, normalisation, journal impact factors and other journal metrics, visualising and mapping science, evaluation and policy, and future developments

Gender disparities and positioning in collaborative hospitality and tourism research

Purpose: To explore gender disparities in the production of tourism knowledge with particular reference to academic journals. Design/methodology/approach: Authorship and co-authorship analyses were conducted of data extracted from articles and research notes published between 1965 and 2016 in 25 hospitality and tourism journals. Findings: Gender imbalances are evident in the production of knowledge, though the disparities appear to be decreasing. While heterophilic research collaborations (those between men and women) show some evidence of higher productivity, homophilic collaborations (between males) have greater impact. The findings highlight gender imbalances in international collaborations, in SSCI listed journals, in first authoring, and by country. There is evidence of higher collaborative levels amongst male authors and the differences have increased over time. The positioning of men and women within tourism scholarly networks shows no marked differences. Practical Implications: This data-driven analysis provides decision-makers and policymakers with evidence to support well targeted programs that advance female contributions in hospitality and tourism research collaborations. For example, senior academics and University administrators might offer support for female researchers to become more actively involved in hospitality and tourism research groups and projects. Universities or schools might also seek to encourage collaborations between male and female researchers in their performance indicators. Originality/Value: This study is one of the first to examine gender disparities and positioning in collaborative hospitality and tourism research