Paper Info
Title
Extraction and Evaluation of Statistical Information from Social and Behavioral Science Papers
Abstract
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.
Year
DOI
Venue
2021
10.1145/3442442.3451363
International World Wide Web Conference
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Sree Sai Teja Lanka100.34
Sarah Michele Rajtmajer23110.06
Jian Wu302.37
C. Lee Giles4111541549.48