An Activity Theory Investigation of Academic Abstract Sentence Classification

Authors

Connor Stead, Macquarie UniversityFollow
Stephen Smith, Macquarie UniversityFollow
Peter Busch, Macquarie UniversityFollow
Savanid Vatanasakdakul, Carnegie Mellon UniversityFollow
Vincent Pang, University of New South WalesFollow

Abstract

This research aims to extend activity theory into the domain of structured abstracts through the examination of the mediating role a software tool providing academic abstract sentence classification capability plays in academic researcher literature discovery. This is motivated by the surge of digitally available academic literature, the high precision of academic abstract sentence classification machine/deep learning models and the absence of literature exploring the deployment of such modelling capability into a tool and its subsequent use to conduct research. This research in progress paper outlines the methodology used in the study, introduces the theoretical framework and software tool and identifies ongoing and future research efforts.

Recommended Citation

Stead, Connor; Smith, Stephen; Busch, Peter; Vatanasakdakul, Savanid; and Pang, Vincent, "An Activity Theory Investigation of Academic Abstract Sentence Classification" (2020). PACIS 2020 Proceedings. 37.
https://aisel.aisnet.org/pacis2020/37