Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/50549

Extracting Causal Claims from Information Systems Papers with Natural Language Processing for Theory Ontology Learning

File Size Format  
paper0662.pdf 744.59 kB Adobe PDF View/Open

Item Summary

Title:Extracting Causal Claims from Information Systems Papers with Natural Language Processing for Theory Ontology Learning
Authors:Mueller, Roland M.
Huettemann, Sebastian
Keywords:Theory and Information Systems
Causal Relationship Extraction, Causality, Natural Language Processing, Theory, Theory Ontology Learning
Date Issued:03 Jan 2018
Abstract:The number of scientific papers published each year is growing exponentially. How can computational tools support scientists to better understand and process this data? This paper presents a software-prototype that automatically extracts causes, effects, signs, moderators, mediators, conditions, and interaction signs from propositions and hypotheses of full-text scientific papers. This prototype uses natural language processing methods and a set of linguistic rules for causal information extraction. The prototype is evaluated on a manually annotated corpus of 270 Information Systems papers containing 723 hypotheses and propositions from the AIS basket of eight. F1-results for the detection and extraction of different causal variables range between 0.71 and 0.90. The presented automatic causal theory extraction allows for the analysis of scientific papers based on a theory ontology and therefore contributes to the creation and comparison of inter-nomological networks.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/50549
ISBN:978-0-9981331-1-9
DOI:10.24251/HICSS.2018.660
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Theory and Information Systems


Please email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.

This item is licensed under a Creative Commons License Creative Commons