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Emerging research topics detection with multiple machine learning models
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DOI：10.1016/j.joi.2019.100983.png)
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Abstract
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Emerging research topic detection can benefit the research foundations and policy-makers. With the long-term and recent interest in detecting emerging research topics, various approaches are proposed in the literature. Though, there is still a lack of well-established linkages between the clear conceptual definition of emerging research topics and the proposed indicators for operationalization. This work follows the definition by Wang (2018), and several machine learning models are together used to detect and foresight the emerging research topics. Finally, experimental results on gene editing dataset discover three emerging research topics, which make clear that it is feasible to identify emerging research topics with our framework. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords:
Emerging research topics
Topic modeling
Dynamic Influence Model
Citation Influence Model
Machine learning
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