Identifying emerging topics in science and technology

Small, Henry; Boyack, Kevin W.; Klavans, Richard

doi:10.1016/j.respol.2014.02.005

Cited by 293 publications

(203 citation statements)

References 35 publications

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“…Specific research areas include text analytics, knowledge discovery, big data, social network analysis, natural language processing, forecasting, and machine learning. According to [Smalla et al, 2014] the programme has a clear link with competitive technical intelligence. The techniques referenced and the automated analysis intent fall within the domain of business analytics but the intent is to create foresight-based conclusions.…”

Section: The Combined Approachmentioning

confidence: 99%

Foresight, Competitive Intelligence and Business Analytics — Tools for Making Industrial Programmes More Efficient

Calof

Richards²,

Smith³

2015

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Creating industrial policy and programmes, especially in technology, is fraught with high levels of uncertainty. These programmes target the development of products that will not be sold for several years; therefore, one of the risks is that the products will no longer be in demand or will have been overtaken by more advanced technologies. In several cases, the authors have seen these programmes fail because the intended targets of the programme did not apply to use the programme funds (poorly targeted program) or did not use the programme properly. An integrated programme involving foresight, competitive intelligence and business analytics assists in decreasing the probability of the risks and problems described above, resulting in better designed and more successful industrial policy. These techniques can also be used to create a dashboard for monitoring programme use so that any problems can be corrected early on. The dashboard uses advanced analytics to assess programme applications and programme inquiries to assess whether the programme is being used properly. Via an integrated intelligence process, it monitors the external environment to ensure that programme assumptions in terms of what technologies are most appropriate remain valid. The dashboard relies on information available in open sources and available to the government.

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Section: The Combined Approachmentioning

confidence: 99%

Foresight, Competitive Intelligence and Business Analytics — Tools for Making Industrial Programmes More Efficient

Calof

Richards²,

Smith³

2015

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“…Within the framework of carbonbased materials, however, this 2-D material suddenly aroused the attention of scientists (Lv et al, 2011). With the experimental discovery of graphene by Novoselov et al (2004), a rapidly growing stream of scientific literature became fertile land for bibliometric studies: Barth and Marx (2008), Wan and Pan (2010), Shapira et al (2010), Lv et al (2011), Munoz-Sandoval (2014), Small et al (2014), Terekhov (2015), Klincewicz (2016), and Shapira et al (2016).…”

mentioning

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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“…The reviewed methodologies rely on different models, data, thresholds, clustering algorithms and parameters, the selection of which may bias the detection of emergence towards certain patterns. Small et al (2014), for example, found that topics identified as emerging by the combined 'direct citation-co-citation' approach are in areas that are more likely to offer practical outcomes than non-emerging topics. This may suggest that such areas attract more resources, which, in turn, may favour the recruitment of researchers ).…”

Section: Discussionmentioning

confidence: 99%

What is an Emerging Technology?

2015

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There is considerable and growing interest in the emergence of novel technologies, especially from the policy-making perspective. Yet as an area of study, emerging technologies lacks key foundational elements, namely a consensus on what classifies a technology as 'emergent' and strong research designs that operationalize central theoretical concepts. The present paper aims to fill this gap by developing a definition of 'emerging technologies' and linking this conceptual effort with the development of a framework for the operationalisation of technological emergence. The definition is developed by combining a basic understanding of the term and in particular the concept of 'emergence' with a review of key innovation studies dealing with definitional issues of technological emergence. The resulting definition identifies five attributes that feature in the emergence of novel technologies. These are: (i) radical novelty, (ii) relatively fast growth, (iii) coherence, (iv) prominent impact, and (v) uncertainty and ambiguity. The framework for operationalising emerging technologies is then elaborated on the basis of the proposed attributes. To do so, we identify and review major empirical approaches (mainly in, although not limited to, the scientometric domain) for the detection and study of emerging technologies (these include indicators and trend analysis, citation analysis, co-word analysis, overlay mapping, and combinations thereof) and elaborate on how these can be used to operationalise the different attributes of emergence.

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Identifying emerging topics in science and technology

Cited by 293 publications

References 35 publications

Foresight, Competitive Intelligence and Business Analytics — Tools for Making Industrial Programmes More Efficient

Foresight, Competitive Intelligence and Business Analytics — Tools for Making Industrial Programmes More Efficient

Identification and Visualization of the Intellectual Structure in Graphene Research

What is an Emerging Technology?

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