Extraction and Evaluation of Statistical Information from Social and Behavioral Science Papers

Sree Sai Teja Lanka, Sarah Rajtmajer, Jian Wu, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With substantial and continuing increases in the number of published papers across the scientific literature, development of reliable approaches for automated discovery and assessment of published findings is increasingly urgent. Tools which can extract critical information from scientific papers and metadata can support representation and reasoning over existing findings, and offer insights into replicability, robustness and generalizability of specific claims. In this work, we present a pipeline for the extraction of statistical information (p-values, sample size, number of hypotheses tested) from full-Text scientific documents. We validate our approach on 300 papers selected from the social and behavioral science literatures, and suggest directions for next steps.

Original languageEnglish (US)
Title of host publicationThe Web Conference 2021 - Companion of the World Wide Web Conference, WWW 2021
PublisherAssociation for Computing Machinery, Inc
Pages426-430
Number of pages5
ISBN (Electronic)9781450383134
DOIs
StatePublished - Apr 19 2021
Event30th World Wide Web Conference, WWW 2021 - Ljubljana, Slovenia
Duration: Apr 19 2021Apr 23 2021

Publication series

NameThe Web Conference 2021 - Companion of the World Wide Web Conference, WWW 2021

Conference

Conference30th World Wide Web Conference, WWW 2021
Country/TerritorySlovenia
CityLjubljana
Period4/19/214/23/21

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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