Category Archives: Citation analysis

Medicine-Engineering Interdisciplinary Research Based on Bibliometric Analysis: A Case Study on Medicine-Engineering Institutional Cooperation of Shanghai Jiao Tong University (Full-Text)

Citation analysis, Interdisciplinarity, Research Examples, Research profiling, VOSViewer

This article aims to provide reference for medicine-engineering interdisciplinary research. Targeted at
the scientific literature and patent literature published by Shanghai Jiao Tong University, this article attempts to set up co-occurrence matrix of medicine-engineering institutional information which was extracted from address fields of the papers, so as to construct the medicine-engineering intersection datasets. The dataset of scientific literature was analyzed using bibliometrics and visualization methods from multiple dimensions, and the most active factors, such as trends of output, journal and subject distribution, were identified from the indicators of category normalized citation impact (CNCI), times cited, keywords, citation topics and the degree of medicine engineering interdisplinarity. Research on hotspots and trends was discussed in detail. Analyses of the dataset of patent literature showed research themes and measured the degree for technology convergence of medicine engineering.

For FULL-TEXT https://doi.org/10.1007/s12204-022-2418-5

Author(s): WANG Qingwen, CUI Tingting, DENG Peiwen
Organization(s): Shanghai Jiao Tong University
Source: Journal of Shanghai Jiao Tong University
Year: 2022

Learning about learning: patterns of sharing of research knowledge among Education, Border, and Cognitive Science fields

Citation analysis, Research Examples, ST&I indicators

This study explores the patterns of exchange of research knowledge among Education Research, Cognitive Science, and what we call “Border Fields.” We analyze a set of 32,121 articles from 177 selected journals, drawn from five sample years between 1994 and 2014. We profile the references that those articles cite, and the papers that cite them. We characterize connections among the fields in sources indexed by Web of Science (WoS) (e.g., peer-reviewed journal articles and proceedings), and connections in sources that are not (e.g., conference talks, chapters, books, and reports). We note five findings—first, over time the percentage of Education Research papers that extensively cite Cognitive Science has increased, but the reverse is not true. Second, a high percentage of Border Field papers extensively cite and are cited by the other fields. Border Field authors’ most cited papers overlap those most cited by Education Research and Cognitive Science. There are fewer commonalities between Educational research and Cognitive Science most cited papers. This is consistent with Border Fields being a bridge between fields. Third, over time the Border Fields have moved closer to Education Research than to Cognitive Science, and their publications increasingly cite, and are cited by, other Border Field publications. Fourth, Education Research is especially strongly represented in the literature published outside those WoS-indexed publications. Fifth, the rough patterns observed among these three fields when using a more restricted dataset drawn from the WoS are similar to those observed with the dataset lying outside the WoS, but Education Research shows a far heavier influence than would be indicated by looking at WoS records alone.

https://doi.org/10.1007/s11192-019-03012-3

Author(s): Alan L. Porter, David J. Schoeneck, Jan Youtie, Gregg E. A. Solomon, Seokbeom Kwon, Stephen F. Carley
Organization(s): Search Technology, Georgia Tech, US National Science Foundation
Source: Scientometrics
Year: 2019

What people learn about how people learn: An analysis of citation behavior and the multidisciplinary flow of knowledge

Citation analysis, Interdisciplinarity, Research Examples, Research Type, ST&I indicators

We explore the contention that the seminal US National Academies consensus report,How People Learn(HPL),played a major role in bridging the flow of knowledge from Cognitive Science to Education. Our paper yielded four important results: First, HPL is, on a number of bibliometric measures, an unusually interdisciplinary work.Focusing on the fields of particular interest here, our citation analysis shows the Education, Cognitive Science,and Borderfield (e.g., Educational Psychology, Learning Sciences, and Learning Technology and Human-Computer Interaction) literatures all to have been major influences on it. Second, we found HPL to be unusually highly cited–and by publications from an unusually diverse set of disciplines. Beyond Education, Cognitive Science, and Border field publications, HPL was also relatively highly cited by publications in Medical/Health-related, Engineering, and other Discipline-Based Education Research fields. Third, undermining the claim that HPL served as a gateway to the Cognitive Science literature, we found Education articles citing HPL not to be more likely to have Cognitive Science as a major influence than are Education articles more generally, as in-dicated by their cited references. Finally, the Education publications that cited HPL were far more likely to refer to concepts in HPL that were already prevalent in the Education literature rather than to concepts from Cognitive Science. Conversely, the Cognitive Science publications that cited HPL were more apt to refer to concepts already in the Cognitive Science literature. Taken together, these results are a caution that, even for a highly regarded multidisciplinary work cited widely by publications from multiple disciplines, its direct influence could be largely disciplinary. Implications for the policy goals of fostering interdisciplinary research and the role of National Academies consensus reports are discussed.

https://doi.org/10.1016/j.respol.2019.103835

Author(s): Gregg E. A. Solomon, Jan Youtie, Stephen Carley, Alan L. Porter  
Organization(s): National Science Foundation, Georgia Institute of Technology                                                                                                        
Source: Research Policy                                                                                       
Year: 2019

Research addressing emerging technological ideas has greater scientific impact

Citation analysis, Research Examples, Research Type, ST&I indicators,

This study empirically examines the association between the extent of emerging technological ideas in a scientific publication and its future scientific impact measured by number of citations. We analyze metadata of scientific publications in three scientific domains: Nano-Enabled Drug Delivery, Synthetic Biology, and Autonomous Vehicles. By employing a bibliometric indicator for identifying and quantifying emerging technological ideas – as derived terms from the titles and abstracts – we measure the extent to which the publication contains emerging technological ideas in each domain. Then, we statistically estimate the size and statistical significance of the relationship between the publication-level technological emergence score and the normalized number of citations accruing to the publication.

Our analysis shows that the degree to which a paper contains technologically emerging ideas is positively and strongly associated with its future citation impact in each of the three domains. An additional analysis demonstrates that this relationship holds for citations from other publications, both in the same field as, and in different fields from, the scientific domain of the focal publication. A series of tests for validation further support our argument that the greater the extent to which scientific knowledge (a paper) contains emerging ideas, the bigger its scientific impact. Implications for academic researchers, research policymakers, and firms are discussed.

https://doi.org/10.1016/j.respol.2019.103834

Author(s): Seokbeom Kwon, Xiaoyu Liu, Alan L. Porter, Jan Youtie
Organization(s): Georgia Institute of Technology, Beijing Institute of Technology
Source: Research Policy
Year: 2019

Qualitative Patents Evaluation Through the Analysis of Their Citations. Case of the Technological Sectors in the Basque Country

Citation analysis, Patents, Research Examples, ST&I indicators

Patents are an output of the level of innovation of a company or region. Patent quantitative studies are performed by simply counting the number of these documents. For the qualitative evaluation, there is a certain consensus among the authors to consider the citations as the most adequate indicator. However, this indicator presents several problems regarding its correct interpretation. In the present study, in order to avoid the typical citation interpretation biases, a precise methodology is presented. As an illustrative example, we present a comparative study of the quality of patents in technological sectors of the Basque Country region over the period 1991–2011.

DOI
https://doi.org/10.1007/978-3-319-96005-0_28

Author(s): J. Gavilanes-Trapote, Ernesto Cilleruelo-Carrasco, I. Etxeberria-Agiriano, Gaizka Garechana, Alejandro Rodríguez Andara
Organization(s): University of the Basque Country
Source: Engineering Digital Transformation. Lecture Notes in Management and Industrial Engineering. Springer, Cham
Year: 2018

Research network emergence: societal issues in nanotechnology and the center for nanotechnology in society

Citation analysis, Network analysis, Research Examples

This article looks at the creation of a network of researchers of social issues in nanotechnology and the role of the Center for Nanotechnology in Society at Arizona State University (CNS-ASU) in the creation of this network. The extent to which CNS-ASU is associated with the development of a research network around the study of social issues in nanotechnology is examined through geographic mapping of co-authors and citations of center publications, network analysis of co-authors of papers on social issues in nanotechnology, and a disciplinary analysis of these papers. The results indicate that there is an extensive network of co-authorships among researchers studying social issues in nanotechnology with CNS-ASU at the center of this network. In addition, papers written by center members and affiliates integrate a diverse range of disciplines. Qualitative data are used to interpret some of the ways that citation occurs.

https://doi.org/10.1093/scipol/scy043

Author(s): Jan Youtie, Philip Shapira, Michael Reinsborough, Erik Fisher
Organization(s): Georgia Institute of Technology, Arizona State University
Source: Science and Public Policy
Year: 2018

Innovation core, innovation semi-periphery and technology transfer: The case of wind energy patents

Citation analysis, Network analysis, Research Type, Strategic planning

Some scholars have pointed to a rise of South-South technological transfer led by emerging economies such as China, India, Brazil and South Africa while other scholars highlight that emerging economies still need to catch up with developed countries. Drawing on world system’s theory, we argue that an adapted innovation framework of ‘core – semi-periphery – periphery’ could be an important analytical framework that may help us understand the process of innovation catch up. This may help specifically to better understand how an emerging economy can at least in theory have sectors that could be defined as innovation core and source for technology transfer. We will look at wind energy as North American, European, Indian and Chinese firms dominate the market. This study used citation network analysis and patent analysis to analyse knowledge flows between wind firms and to identify and compare the position and role of each firm in the knowledge network. We argue that there is still, despite catching up, a difference between innovation core countries (US, Germany, Denmark) and innovation semi-periphery (China, India) which will limit the opportunities of knowledge transfer within the sector of wind energy.

https://doi.org/10.1016/j.enpol.2018.04.048

Author(s): Johan Nordensvard, Yuan Zhou, Xiao Zhang
Organization(s): University of Southampton, Tsinghua University
Source: Energy Policy
Year: 2018

Insights into relationships between disruptive technology/innovation and emerging technology: A bibliometric perspective

Citation analysis, Research Examples, Research Type

“Disruptive technology & disruptive innovation” have been of scholarly interest for years, but there is still a need to better understand the nature of disruptions and their relationship to emerging technology processes. This paper pursues these issues by analyzing the interplay of technological emergence, disruption, and innovation. Applying bibliometric methods, the paper explores the conceptual foundations, themes, and research communities within these research domains. Co-citation analyses point to three largely distinct communities on disruptive technology/innovation and emerging technology. The results highlight the multiple theoretical foundations of research around technological change processes, disruption, and emergence. These differences among the domains invite conceptual cross-fertilization and consideration of interdisciplinary approaches to technological (and commercial) emergence.

https://doi.org/10.1016/j.techfore.2017.09.032

Author(s): Munan Li, Alan L. Porter, Arho Suominen
Organisation(s): South China University of Technology, Georgia Institute of Technology, VTT Technical Research Centre of Finland
Source: Technological Forecasting & Social Change
Year: 2018

Big Data in the Social Sciences

Citation analysis, Research Examples, Research profiling

Recent emerging technology policies seek to diminish negative impacts while equitably and responsibly accruing and distributing benefits.  Social scientists play a role in these policies, but relatively little quantitative research has been performed to study how social scientists inform the assessment of emerging technologies. This paper addresses this gap by examining social science research on “Big Data” – an emerging technology of wide interest. This paper analyzes a dataset of fields extracted from 488 social science and humanities papers written about Big Data. Our focus is on understanding the multi-dimensional nature of societal assessment by examining the references upon which these papers draw. We find that eight sub-literatures are important in framing social science research about Big Data. These results indicate that the field is evolving from general sociological considerations toward applications issues and privacy concerns. Implications for science policy and technology assessment of societal implications are discussed.

Preprint available at http://works.bepress.com/jan_youtie/80/

Author(s): Jan Youtie and Alan Porter
Organizations: Georgia Institute of Technology
Source: Science and Public Policy
Year: 2016

Nano/micro-electro mechanical systems: a patent view

Citation analysis, CTI, Patents, Research Examples, Research profiling, Research Type, Strategic planning

Combining both bibliometrics and citation network analysis, this research evaluates the global development of micro-electro mechanical systems (MEMS) research based on the Derwent Innovations Index database. We found that worldwide, the growth trajectory of MEMS patents demonstrates an approximate S shape, with United States, Japan, China, and Korea leading the global MEMS race. Evidenced by Derwent class codes, the technology structure of global MEMS patents remains steady over time. Yet there does exist a national competitiveness component among the top country players. The latecomer China has become the second most prolific country filing MEMS patents, but its patent quality still lags behind the global average.

http://link.springer.com/article/10.1007/s11051-015-3273-1

Author(s): Guangyuan Hu and Weishu Liu
Organization(s): Shanghai University of Finance and Economics,Shanghai Jiao Tong University
Source: Journal of Nanoparticle Research
Year: 2015