Large-scale temporal analysis of computer and information science

Soós, Sándor; Kampis, George; Gulyás, László

doi:10.1140/epjst/e2013-01936-6

Cited by 7 publications

(5 citation statements)

References 18 publications

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“…Keywords have as their main objective to provide rapid access to scientific works (Soos et al, 2013). Author Keywords provide the "author aboutness, " that is, contents expressed through terms in natural language, while Indexed Keywords give the interpretation of contents (Stock and Stock, 2013).…”

Section: Methodsmentioning

confidence: 99%

Identification and Visualization of the Intellectual Structure in Graphene Research

Vargas-Quesada

Chinchilla‐Rodríguez

Rodríguez

2017

Front. Res. Metr. Anal.

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Since the discovery of the promising properties of graphene, research in the field has attracted numerous grants and sponsors, leading to an exponential rise in the number of papers and applications. This article presents a global map of graphene research and its intellectual structure, drawn using the terms of more than 50,000 documents extracted from Scopus database, years 1998-2015. The unit of analysis consisted of descriptors (including Author Keywords and Indexed Keywords), with the co-occurrence of descriptor as the unit of measure, using fractional counting. The main research lines identified are: Fundamental Research, Functionalization and Biomedical Applications, Technology and Devices, Materials Science, Energy Storage, Optics and Chemical Properties and Sensors. Using overlay maps, we depict the graphene research efforts of the United States, the European Union (Europe-28), and China, and project their evolution through longitudinal maps to facilitate comparison. The United States was initially at the head of world output in graphene research, but was surpassed by China in 2011 and by Europe in 2014, as a result of their respective scientific policies and financial support. The output of China has since been so intense that it can be said to mark graphene research trends. We believe this information may be valuable for the core community involved in this scientific field, as it offers a large-scale analysis showing how research has changed over time. It is therefore also helpful for policy makers and research planners. The resulting maps are a useful and attractive tool for the graphene research community, as they reveal the main lines of exploration at a glance. The methodology described here could be re-created in any other field of science to uncover and display its intellectual structure and evolution over time.

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Section: Methodsmentioning

confidence: 99%

Identification and Visualization of the Intellectual Structure in Graphene Research

Vargas-Quesada

Chinchilla‐Rodríguez

Rodríguez

2017

Front. Res. Metr. Anal.

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“…It identified publications mentioning the insula in their titles, abstracts, author keywords or KeyWord Plus (keywords indexed by WoS). Keywords serve the function of providing rapid access to scientific works (Soos et al, 2013 ) and are useful for bibliometric analyses (Stock and Stock, 2013 ; Zhang et al, 2016 ; Vargas-Quesada et al, 2017 ), and thus were considered together with abstracts and titles. No other restriction was placed on the search, such as publication year.…”

Section: Methodsmentioning

confidence: 99%

The 100 Most Cited Papers Concerning the Insular Cortex of the Brain: A Bibliometric Analysis

Yeung

2018

Front. Hum. Neurosci.

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Background: The insula is one of the most researched brain regions with many highly cited papers. However, unlike the literature of other fields, there is currently no study that has identified the 100 most cited papers within the literature of the insula. The aim of the current study was to fill in the knowledge gap by determining which publications concerning the insula have been cited most often, who contributed to them, and what topics they were dealing with.Methods: The Web of Science online database was searched to identify the 100 most cited publications mentioning the insular cortex in their titles, abstracts or keywords. To systematically exclude irrelevant publications, the search strategy was finalized as: TS = (insula OR insular OR “island of Reil”) NOT TS = (“insular biogeography” OR “insular mammal*” OR “*insular lymphatic*”) NOT WC = (“Geochemistry and Geophysics” OR “Ecology”). The identified publications were sorted in descending order of citation count. The 100 most cited publications concerning the insula of the brain were identified and their bibliometric data was extracted and assessed. The VOSviewer software was used with default parameters to generate a bubble map that analyzes and visualizes the words/phrases used in the titles and abstracts of the publications.Results: There were 67 articles on experiments/lab studies and 33 meta-analyses/reviews but no opinion or methods paper. They had an average of 943.4 citations (or 62.9 citations per year), 93.5 references and 13.4 pages. There were 35 papers published in open access. USA was the major contributing country. The most top-ranked publications were concerning emotion, salience and pain.Conclusion: Two-thirds of the publications concerned the normal brain function/mechanism (n = 67), whereas 20 publications concerned disease/therapeutic intervention and another 13 concerned normal anatomy. For the 67 original articles, 57 used human subjects whereas 10 used animal models. MRI was the commonest modality (n = 37), followed by PET (n = 16). Nine articles investigated by histology, two by multiple modalities and three by other modality.

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“…Bibliometric research uses quantitative analysis of statistical data in published literature to study publication patterns within a scientific field (De Bellis, 2009). In general, bibliometric studies can be divided into two broad categories (Soos et al, 2013): evaluative bibliometric studies (designed to measure the impact of research with the purpose of evaluating science through the use of quantitative indicators), and structural bibliometric studies (through the use of relational indicators based on the co-occurrence of certain units of analysis, such as citations, authors or keywords). Another classification, proposed by Van Raan (2005), is based on bibliometric indicators or statistical data derived from scientific publications: one classification being one-dimensional indicators (based on univariate statistical techniques, dedicated to analysing or measuring a single characteristic of published documents, without considering any link that may exist between them) and the other being multidimensional indicators (based on multivariate statistical techniques, dedicated to analysing or simultaneously measuring different characteristics or variables, or multiple interrelations that could be observed in the published documents).…”

Section: Bibliometric Research Based On Co-word Analysismentioning

confidence: 99%

Evolution of the Field of Social Media Research through Science Maps (2008-2017)

Gálvez¹

2019

Communication & Society

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The objectives of this work were to discover the main points of interest in the field of research on Social Media, within the scientific area of Communication, and to analyse how it has evolved. A methodology based on the analysis of co-words and visualisation techniques was applied. The data was obtained from scientific publications indexed in the Web of Science (WoS) database, during the periods 2008-2012 and 2013-2017. The resulting maps showed that, during the period 2008-2012, the main areas of interest were web 2.0 and the internet in terms of social networking sites. However, during the period 2013-2017, there was a strong upward trend in the impact of social networks and platforms, especially Twitter and Facebook, in many areas (such as social movements, public relations and publicity, distribution of content, crisis communication, participatory journalism, political communication, or the configuration of public identities through social platforms, with special emphasis on youth). Finally, new scientific challenges were found in automatic analysis of content and management of big data. In conclusion, it was possible to transform a complex, underlying, dynamic and multidimensional reality into visible representations that could help experts in the field to better understand the evolution of research on Social Media.

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Large-scale temporal analysis of computer and information science

Cited by 7 publications

References 18 publications

Identification and Visualization of the Intellectual Structure in Graphene Research

Identification and Visualization of the Intellectual Structure in Graphene Research

The 100 Most Cited Papers Concerning the Insular Cortex of the Brain: A Bibliometric Analysis

Evolution of the Field of Social Media Research through Science Maps (2008-2017)

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