Identifying emerging topics in a technological domain

Zhang, Shengtai; Fang, Han

doi:10.3233/jifs-169054

Cited by 4 publications

(3 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Direct citation networks, co-citation networks, and coupling networks are the three main categories of citation networks. The direct citation network method refers to identifying emerging technical topics based on patent direct citation network clustering analysis [37]. The co-citation network method clusters and evaluates the co-citation relationships among "hot patents" and extracts the set of technologies among them [38].…”

Section: Insufficient Indication Of Important Low-frequency Wordsmentioning

confidence: 99%

Technical Trends and Competitive Situation in Respect of Metahuman—From Product Modules and Technical Topics to Patent Data

et al. 2022

View full text Add to dashboard Cite

As a form of technological integration, metahuman has a significant influence on sustainable production because of its consistent technological evolution. However, few studies have provided insights into the technical assessment of metahuman by employing patents. In this paper, patent analysis is conducted to identify technological trends and the competitive situation in respect of metahuman from a product modularity perspective. First, we identify 17 highly relevant metahuman keywords by combining a literature analysis and an expert interview method and identify 42,256 patents from the Derwent Innovation Index (DII), thus improving the accuracy and validity of the data collection process. Then, metahuman product modularity is implemented using the function-behavior-structure (FBS) model, and seven technical topics are extracted from patents via latent Dirichlet allocation (LDA). Lastly, the procedure for identifying technology areas in respect of metahuman is improved by applying an optimized method to establish the connecting paths of product modules, technical topics, and patent data. The analysis results show that the development of metahuman technology can be divided into three periods. Different patent priority countries have distinctive competitive advantages and characteristics at the product module level. The findings of this study are intended to aid R&D enterprises and the government in formulating sustainable decision-making and promoting the development of the metahuman industry.

show abstract

Section: Insufficient Indication Of Important Low-frequency Wordsmentioning

confidence: 99%

Technical Trends and Competitive Situation in Respect of Metahuman—From Product Modules and Technical Topics to Patent Data

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Bibliometric approaches that quantitatively analyze publication, patent, and other research output indicators are commonly applied to comprehend the scale and direction of research and innovation in emerging domains of science and technology (Moed et al 2004 ; Small et al 2014 ). Emergent domains are intrinsically characterized by ambiguity about the sources and nature of domain novelty, contestations with established fields, uncertainty about coherence and growth trajectories, and resultant blurriness in domain delineation (Cozzens et al 2010 ; Small et al 2014 ; Zhang et al 2014 , 2016 ; Rotolo et al 2015 ). Definitional problems are compounded where, as is often the case, emerging domains of science and technology span or arise from multiple disciplinary fields (Wagner, et al 2011 ).…”

Section: Synthetic Biology Bibliometric Search Approachmentioning

confidence: 99%

Tracking the emergence of synthetic biology

2017

View full text Add to dashboard Cite

Synthetic biology is an emerging domain that combines biological and engineering concepts and which has seen rapid growth in research, innovation, and policy interest in recent years. This paper contributes to efforts to delineate this emerging domain by presenting a newly constructed bibliometric definition of synthetic biology. Our approach is dimensioned from a core set of papers in synthetic biology, using procedures to obtain benchmark synthetic biology publication records, extract keywords from these benchmark records, and refine the keywords, supplemented with articles published in dedicated synthetic biology journals. We compare our search strategy with other recent bibliometric approaches to define synthetic biology, using a common source of publication data for the period from 2000 to 2015. The paper details the rapid growth and international spread of research in synthetic biology in recent years, demonstrates that diverse research disciplines are contributing to the multidisciplinary development of synthetic biology research, and visualizes this by profiling synthetic biology research on the map of science. We further show the roles of a relatively concentrated set of research sponsors in funding the growth and trajectories of synthetic biology. In addition to discussing these analyses, the paper notes limitations and suggests lines for further work.

show abstract

“…However, the effectiveness of any approach for identification is extremely difficult to verify. And such approaches tend to focus on measuring the attributes of novelty and fast growth, and to ignore the consideration of other potentially important attributes, such as impact [7]. After the small-world model proposed by Watts and Strogatz, Barabá si and Albert (BA) proposed the scale-free network [8].…”

Section: Introductionmentioning

confidence: 99%

An Evolving Hypernetwork Model to Quantify Progress Potential of Emerging Research Topic

Liu

Yang

et al. 2018

MATEC Web Conf.

View full text Add to dashboard Cite

There is considerable and growing interest in the emergence of research topics. However, current methods to detect the emergence are still problematic mainly due to information loss and aging effect. In this study, we show three intrinsic mechanisms including preferential attachment, exponentially growth and heterogeneous fitness values that decay with time. Depending on the input assumptions, all topics tend to follow a universal temporal pattern according to our model which results in strongly sufficiency to quantify progress potential.

show abstract

Identifying emerging topics in a technological domain

Cited by 4 publications

References 20 publications

Technical Trends and Competitive Situation in Respect of Metahuman—From Product Modules and Technical Topics to Patent Data

Technical Trends and Competitive Situation in Respect of Metahuman—From Product Modules and Technical Topics to Patent Data

Tracking the emergence of synthetic biology

An Evolving Hypernetwork Model to Quantify Progress Potential of Emerging Research Topic

Contact Info

Product

Resources

About