Classifying the Ideational Impact of IS Review Articles: A Natural Language Processing Based Approach

Presenter Information

Julian Prester, UNSW Business School, UNSW SydneyFollow
Gerit Wagner, University of RegensburgFollow
Guido Schryen, Paderborn UniversityFollow

Description

By providing knowledge contributions and stimulating future research, review articles (RAs) play a vital role for cumulative knowledge development. Although many papers cite RAs, it is rarely transparent to which degree citation impact represents perfunct

Recommended Citation

Prester, Julian; Wagner, Gerit; and Schryen, Guido, "Classifying the Ideational Impact of IS Review Articles: A Natural Language Processing Based Approach" (2018). ICIS 2018 Proceedings. 1.
https://aisel.aisnet.org/icis2018/research/Presentations/1