pyResearchInsights—An open‐source Python package for scientific text analysis

With an increasing number of scientific articles published each year, there is a need to synthesize and obtain insights across ever‐growing volumes of literature. Here, we present pyResearchInsights, a novel open‐source automated content analysis package that can be used to analyze scientific s with...

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Vydáno v:Ecology and evolution Ročník 11; číslo 20; s. 13920 - 13929
Hlavní autoři: Shetty, Sarthak J., Ramesh, Vijay
Médium: Journal Article
Jazyk:angličtina
Vydáno: England John Wiley & Sons, Inc 01.10.2021
John Wiley and Sons Inc
Wiley
Témata:
automated content analysis
Automation
Biodiversity
Biodiversity hot spots
Biology
Birds
Case studies
Climate change
Conservation
Conservation biology
Content analysis
Data mining
Environmental policy
exploratory analysis
Landscape ecology
Landscape preservation
Natural language processing
Original Research
Plant ecology
Scientific papers
Text analysis
Utilities
natural language processing
exploratory analysis
automated content analysis
ISSN:2045-7758, 2045-7758
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Popis
Shrnutí:With an increasing number of scientific articles published each year, there is a need to synthesize and obtain insights across ever‐growing volumes of literature. Here, we present pyResearchInsights, a novel open‐source automated content analysis package that can be used to analyze scientific s within a natural language processing framework. The package collects s from scientific repositories, identifies topics of research discussed in these s, and presents interactive concept maps to visualize these research topics. To showcase the utilities of this package, we present two examples, specific to the field of ecology and conservation biology. First, we demonstrate the end‐to‐end functionality of the package by presenting topics of research discussed in 1,131 s pertaining to birds of the Tropical Andes. Our results suggest that a large proportion of avian research in this biodiversity hotspot pertains to species distributions, climate change, and plant ecology. Second, we retrieved and analyzed 22,561 s across eight journals in the field of conservation biology to identify twelve global topics of conservation research. Our analysis shows that conservation policy and landscape ecology are focal topics of research. We further examined how these conservation‐associated research topics varied across five biodiversity hotspots. Lastly, we compared the utilities of this package with existing tools that carry out automated content analysis, and we show that our open‐source package has wider functionality and provides end‐to‐end utilities that seldom exist across other tools. With an increasing number of scientific articles being published each year, there is a need to synthesize and obtain insights across large volumes of literature. Hence, we developed pyResearchInsights, a novel open‐source, modular, end‐to‐end automated content analysis package that can be used to analyze scientific s within a natural language processing framework.
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ISSN:2045-7758
2045-7758
DOI:10.1002/ece3.8098