Abstract
The number of research publications is growing exponentially, also in the discipline of Information Systems (IS). Evidently, we need new automated means for carrying out extensive inquiries into bodies of knowledge to understand the thematic foci of publications. The aim of this study is to apply an automated cluster analysis as a method of text mining and identify thematic foci of 654 BLED conference proceedings obtained from Scopus since 2005. Subsequently, we discuss advantages and challenges associated with the automatic analysis of huge volumes of texts. Our results support scientists and practitioners to focus future research efforts on these topics and thus help to establish and investigate the identity of the IS discipline, particularly against the background of the growing diversity of topics. The results help the conference to align future calls accordingly. In the future, a prototype can be implemented based on the results to suggest suitable search results.
Recommended Citation
Fteimi, Nora; Heikkilä, Marikka; and Heikkilä, Jukka, "Topical Research Cluster of BLED Community – A Text Mining Approach" (2020). BLED 2020 Proceedings. 9.
https://aisel.aisnet.org/bled2020/9