Work Description

Title: Supporting Data for "Multi-level computational methods for interdisciplinary research in the HathiTrust Digital Library" Open Access Deposited

https://creativecommons.org/publicdomain/zero/1.0/
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Abstract
  • We show how faceted search using a combination of traditional classification systems and mixed-membership topic models can go beyond keyword search to inform resource discovery, hypothesis formulation, and argument extraction for interdisciplinary research. Our test domain is the history and philosophy of scientific work on animal mind and cognition. The methods can be generalized to other research areas and ultimately support a system for semi-automatic identification of argument structures. We provide a case study for the application of the methods to the problem of identifying and extracting arguments about anthropomorphism during a critical period in the development of comparative psychology. We show how a combination of classification systems and mixed-membership models trained over large digital libraries can inform resource discovery in this domain. Through a novel approach of ``drill-down'' topic modeling---simultaneously reducing both the size of the corpus and the unit of analysis---we are able to reduce a large collection of fulltext volumes to a much smaller set of pages within six focal volumes containing arguments of interest to historians and philosophers of comparative psychology. The volumes identified in this way did not appear among the first ten results of the keyword search in the HathiTrust digital library and the pages bear the kind of "close reading" needed to generate original interpretations that is the heart of scholarly work in the humanities. Zooming back out, we provide a way to place the books onto a map of science originally constructed from very different data and for different purposes. The multilevel approach advances understanding of the intellectual and societal contexts in which writings are interpreted.
Description
  • Supporting datasets for drill-down topic modeling workflow described in "Multi-level computational methods for interdisciplinary research in the HathiTrust Digital Library." PLOS ONE.  https://doi.org/10.1371/journal.pone.0184188
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Last modified
  • 06/20/2024
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Date issued
  • 2017
Description sponsorship
  • National Endowment for Humanities (NEH) Office of Digital Humanities (ODH) Digging Into Data Challenge ("Digging by Debating"; PIs Allen, Börner, Ravenscroft, Reed, and Bourget; award no. HJ-50092-12)
To Cite this Work:
Supporting Data for "Multi-level computational methods for interdisciplinary research in the HathiTrust Digital Library" [Data set]. Indiana University - DataCORE.

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Files (Count: 3; Size: 4.17 KB)

Thumbnail Title Original Upload Last Modified File Size Access Actions
plos-models.tar.gz 2024-07-21 2024-07-21 Open Access
manifest.txt 2024-08-16 2024-08-16 154 Bytes Open Access
README.txt 2024-08-16 2024-08-16 4.02 KB Open Access

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