Relative age of references as a tool to identify emerging research fields with an application to the field of ecology and environmental sciences

Jarić, Ivan; Knežević-Jarić, Jelena; Lenhardt, Mirjana

doi:10.1007/s11192-014-1268-9

Cited by 19 publications

(3 citation statements)

References 30 publications

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“…Iwami et al [79] analysed the time transitions of centrality measures to detect the leading article. Jaric ´et al [80] observed how the emerging research subfields were characterised by comparably more recent references and a higher proportion being published in the preceding 2 years. Soriano et al [81] analysed citation patterns and co-occurrence keywords, while assessing their impact and maturity to propose future research ideas related to technological observatories.…”

Section: Identifying Ertsmentioning

confidence: 99%

Breakthrough potential of emerging research topics based on citation diffusion features

Winnink

Pang

et al. 2022

Journal of Information Science

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This article uses the characteristics of citation curves in emerging research topics (ERTs) and combines them with the ERTs’ knowledge bases to draw conclusions by comparing their development patterns. The goal of this study is to enrich the toolset for predicting breakthroughs in scientific research. A set of multidimensional and practical bibliometric indicators is used to identify ERTs, to further identify the knowledge bases of ERTs and construct citation curves for both ERTs and their knowledge bases. The development trends of the citation curves of ERTs and their knowledge bases in different time periods are compared and analysed from two dimensions: knowledge transition and continuous growth. We use the field of stem cell research to test our method. Based on the outcome of the analysis, we can assess the breakthrough potential of ERTs. The stratification, transition and recent changes of the citation curve can be used as a basis for analysing and assessing the ERTs’ breakthrough potential. The combination of different citation diffusion patterns of ERTs and their knowledge bases can improve the effectiveness of identifying ERTs that can become breakthrough innovations.

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Section: Identifying Ertsmentioning

confidence: 99%

Breakthrough potential of emerging research topics based on citation diffusion features

Winnink

Pang

et al. 2022

Journal of Information Science

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“…In that sense, several studies such as the one by Mryglod et al (2016) have called attention to the interest in describing the features of this evolution, given that the results of numerous case studies can be used in detecting the typical patterns, universal for different topics (Mryglod et al, 2016). Researchers like Jarić, Knezević- Jarić & Lenhardt (2014) have also speculated that trends in the relative age of references might be also indicative of emerging research fields. In the present paper, we aim to address both of these aspects.…”

Section: Emerging Topics: Concept and Bibliography Reviewmentioning

confidence: 99%

On the use of bibliometric indicators for the analysis of emerging topics and their evolution: Spin-offs as a case study

González‐Alcaide

Gorraiz

Hervás-Oliver

2018

EPI

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“…Jaric et al observed a consistent pattern to discover the emerging research topics by combining the potential relationships of entities and the relative reference time [29]. Wen et al provided a novel network-based approach to identify biomarders of complex diseases by integrating heterogeneous information, including epigenomic data, gene expression data and a protein–protein interaction network [30].…”

Section: Related Workmentioning

confidence: 99%

The potential relationship discovery model based on result fusion for biomedical medicine research

She

Zhang

Wang

et al. 2015

Journal of Information Science

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With the amount of biomedical data growing explosively, medical scientists use many datasets in research for new medicine. However, the amount of biomedical data is growing too fast to abstract hidden information. At the same time, with the development of data storage diversification, scientists prefer to have data fusion based on heterogeneous data sources as opposed to a single data source, and ultimately to achieve knowledge and discovery across heterogeneous databases. Our study focuses on extending the application of latent semantic analysis methodologies into the area of biomedical research. Our purpose is to develop a model for discovering potential relationships between medicines and diseases based on biomedical latent semantic analysis. This model could be used in constructing link maps for biomedical entities, and provide a theoretical basis and practical support for biomedical scientists in their study of the disease–medicine relationship. In detail, we discuss the study of the integration of the latent semantic analysis model and data fusion methodologies. Our result fusion solution combines scientific literature repositories and a biomedical database based on context and the ABC model, and is supervised by a semi-supervised learning algorithm and data fusion algorithms. The expectation is that fused data could represent multilevel potential relationships between biological entities and related emotional relationship expression. The model is validated by experience and proven to be feasible and effective.

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Relative age of references as a tool to identify emerging research fields with an application to the field of ecology and environmental sciences

Cited by 19 publications

References 30 publications

Breakthrough potential of emerging research topics based on citation diffusion features

Breakthrough potential of emerging research topics based on citation diffusion features

On the use of bibliometric indicators for the analysis of emerging topics and their evolution: Spin-offs as a case study

The potential relationship discovery model based on result fusion for biomedical medicine research

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