Unveiling Weak Signals of Emergence in Underwater Sensing Research Trends

Authors

  • Ashkan Ebadi Digital Technologies, National Research Council Canada, Canada https://orcid.org/0000-0002-4542-9105
  • Alain Auger Science and Technology Foresight and Risk Assessment Unit, Defence Research and Development Canada, Canada
  • Yvan Gauthier Digital Technologies, National Research Council Canada, Canada

DOI:

https://doi.org/10.47852/bonviewAAES42023902

Keywords:

structural topic modeling, weak signal, natural language processing, emerging research trends, underwater sensing

Abstract

Detecting emerging research trends is crucial as it allows for the proactive identification and monitoring of novel and influential topics in the scientific community. Monitoring research trends aids researchers, institutions, and policymakers in allocating resources, fostering innovation, and staying competitive in rapidly changing scientific landscapes. The growing significance of underwater sensing technologies in various domains has propelled research endeavours aimed at understanding the characteristics of academic discourse in this field. In this work, we comprehensively analyzed the academic research topics related to underwater sensing technologies using advanced computational methodologies. Leveraging natural language processing, topic modelling, and weak signal detection techniques, and focusing on underwater sensing as the case technology, we dissect a large corpus of scholarly articles published between 2007 and 2021 to unveil underlying thematic patterns and emergent trends within this domain while shedding light on signals of emerging technologies. Among the eighty extracted topics, six research topics were identified and recognized as emerging weak signals, and validated by experts. Notably, deep learning for underwater imaging was the only topic that transitioned from being weak to a strong signal in the final period.

 

Received: 22 July 2024 | Revised: 9 October 2024 | Accepted: 15 October 2024

 

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

 

Data Availability Statement

Data available on request from the corresponding author upon reasonable request.

 

Author Contribution Statement

Ashkan Ebadi: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration; Alain Auger: Conceptualization, Validation, Writing - review & editing; Yvan Gauthier: Validation, Writing - review & editing.


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Published

2024-10-22

Issue

Section

Research Articles

How to Cite

Ebadi, A., Auger, A., & Gauthier, Y. (2024). Unveiling Weak Signals of Emergence in Underwater Sensing Research Trends. Archives of Advanced Engineering Science, 1-9. https://doi.org/10.47852/bonviewAAES42023902