Text analysis tools for identification of emerging topics and research gaps in conservation science

Keeping track of conceptual and methodological developments is a critical skill for research scientists, but this task is increasingly difficult due to the high rate of academic publication. As a crisis discipline, conservation science is particularly in need of tools that facilitate rapid yet insig...

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Bibliographic Details
Published in:Conservation biology 2015-12, Vol.29 (6), p.1606-1614
Main Authors: Westgate, Martin J, Barton, Philip S, Pierson, Jennifer C, Lindenmayer, David B
Format: Article
Language:English
Subjects:
Animals
asignación Dirichlet latente
cluster analysis
Conservation biology
Conservation of Natural Resources - methods
Data Mining
ecologists
Ecosystem
ecosystems
Essay
hot topics
indicadores
indicators
Invertebrates - genetics
latent Dirichlet allocation
meta-analysis
monitoring
Plants - genetics
Scientists
Statistics as Topic
surrogates
sustitutos
synthesis
síntesis
temas sobresalientes
Vertebrates - genetics
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Summary:Keeping track of conceptual and methodological developments is a critical skill for research scientists, but this task is increasingly difficult due to the high rate of academic publication. As a crisis discipline, conservation science is particularly in need of tools that facilitate rapid yet insightful synthesis. We show how a common text‐mining method (latent Dirichlet allocation, or topic modeling) and statistical tests familiar to ecologists (cluster analysis, regression, and network analysis) can be used to investigate trends and identify potential research gaps in the scientific literature. We tested these methods on the literature on ecological surrogates and indicators. Analysis of topic popularity within this corpus showed a strong emphasis on monitoring and management of fragmented ecosystems, while analysis of research gaps suggested a greater role for genetic surrogates and indicators. Our results show that automated text analysis methods need to be used with care, but can provide information that is complementary to that given by systematic reviews and meta‐analyses, increasing scientists’ capacity for research synthesis.
ISSN:0888-8892
1523-1739
DOI:10.1111/cobi.12605