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Multi-level computational methods for interdisciplinary research in the HathiTrust Digital Library.

Jaimie Murdock1,2, Colin Allen1,3,4, Katy Börner1,2,5,6

  • 1Program in Cognitive Science, Indiana University, Bloomington, IN, United States of America.

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Summary
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This study introduces faceted search combining classification and topic models to enhance interdisciplinary research discovery. The methods improve finding relevant arguments in historical scientific literature, surpassing traditional keyword searches.

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Area of Science:

  • Digital Humanities
  • History and Philosophy of Science
  • Information Science

Background:

  • Traditional keyword search often fails to capture the nuances required for interdisciplinary research.
  • Resource discovery in specialized fields like the history of animal cognition is challenging.

Purpose of the Study:

  • To demonstrate how faceted search, using classification and topic models, can improve resource discovery and argument extraction.
  • To apply these methods to the history and philosophy of scientific work on animal mind and cognition.
  • To develop a system for semi-automatic identification of argument structures in scholarly texts.

Main Methods:

  • Utilized a combination of traditional classification systems and mixed-membership topic models.
  • Developed a novel
  • drill-down
  • topic modeling approach to refine corpus analysis.
  • Applied methods to a corpus on the history of comparative psychology, focusing on anthropomorphism arguments.

Main Results:

  • Faceted search identified relevant arguments missed by keyword searches in the HathiTrust digital library.
  • The
  • drill-down
  • topic modeling successfully reduced large digital libraries to focal volumes and pages.
  • The approach enabled "close reading" on relevant texts, crucial for humanities scholarship.

Conclusions:

  • Faceted search and topic modeling offer a powerful alternative to keyword search for interdisciplinary resource discovery.
  • The multilevel approach enhances understanding of the intellectual and societal contexts of scientific writings.
  • These methods can be generalized to other research areas for argument extraction and analysis.