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. The 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/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. The 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.