Purpose:This paper proposes a method of detecting emerging trends in research topics from a more micro perspective.Design/methodology/approach:Through co-word clustering to identify research topics and analyzing position changes of topic words in the keywords life-cycle diagram during different time periods,we detected emerging trends in research topics from a more micro perspective.I’he method was applied to the field of nanotechnology to verify its effectiveness and practicability.Findings:The results show that this method can be used to detect emerging trends in research topics from a more micro perspective,as it divides keywords into five categories:Potential keywords,emerging keywords,hot keywords,stable keywords and recession keywords,through which more details of topic changes can be found.Research limitations:We used keywords provided by authors and database indexers for keywords extraction.But this approach may lead to the problem of “indexer effect”.The method may have a limited effect when applied to a disciplinary domain such as mathematics,which evolves slowly.Practical implications:This study provides information analysts with insights into the way to better understand specialty areas of a discipline domain and formulate research policies and strategic plans.Originality/value:This study contributes to the current literature by proposing a new method,which can detect emerging trends in research topics from a more micro perspective. Purpose: This paper proposes a method of detecting emerging trends in research topics from a more micro perspective. Design / methodology / appach: Through co-word clustering to identify research topics and analyzing position changes of topic words in the keywords life-cycle diagram during different time periods, we detected emerging trends in research topics from a more micro perspective. I’he method was applied to the field of nanotechnology to verify its effectiveness and practicability. Findings: The results show that this method can be able to detect emerging trends trends in research topics from a more micro perspective, as it divides keywords into five categories: Potential keywords, emerging keywords, hot keywords, stable keywords and recession keywords, through which more details of topic changes can be found. Research limitations: We used keywords provided by authors and database indexers for keywords extraction.But this approach may lead to the problem of “indexer effect ”. The method may have a li mited effect when applied to a disciplinary domain such as mathematics, which evolves slowly. Practical implications: This study provides information analysts with insights into the way to better understand specialty areas of a discipline domain and formulate research policies and strategic plans. Originality / value: This study contributes to the current literature by proposing a new method, which can detect emerging trends in research topics from a more micro perspective.