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Register a new userTopics Emerged in the Biomedical Field and Their Characteristics
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Added by
Kun Lu
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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This study aims to reveal what kind of topics emerged in the biomedical domain by retrospectively analyzing newly added MeSH (Medical Subject Headings) terms from 2001 to 2010 and how they have been used for indexing since their inclusion in the thesaurus. The goal is to investigate if the future trend of a new topic depends on what kind of topic it is without relying on external indicators such as growth, citation patterns, or word co-occurrences. This topic perspective complements the traditional publication perspective in studying emerging topics. Results show that topic characteristics, including topic category, clinical significance, and if a topic has any narrower terms at the time of inclusion, influence future popularity of a new MeSH. Four emergence trend patterns are identified, including emerged and sustained, emerged not sustained, emerged and fluctuated, and not yet emerged. Predictive models using topic characteristics for emerging topic prediction show promise. This suggests that the characteristics of topics and domain should be considered when predicting future emergence of research topics. This study bridges a gap in emerging topic prediction by offering a topic perspective and advocates for considering topic and domain characteristics as well as economic, medical, and environmental impact when studying emerging topics in the biomedical domain.
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In this study, we apply co-word analysis - a text mining technique based on the co-occurrence of terms - to map the topology of software testing research topics, with the goal of providing current and prospective researchers with a map, and observations about the evolution, of the software testing field. Our analysis enables the mapping of software testing research into clusters of connected topics, from which emerge a total of 16 high-level research themes and a further 18 subthemes. This map also suggests topics that are growing in importance, including topics related to web and mobile applications and artificial intelligence. Exploration of author and country-based collaboration patterns offers similar insight into the implicit and explicit factors that influence collaboration and suggests emerging sources of collaboration for future work. We make our observations - and the underlying mapping of research topics and research collaborations - available so that researchers can gain a deeper understanding of the topology of the software testing field, inspiration regarding new areas and connections to explore, and collaborators who will broaden their perspectives.
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