Topical Research Cluster of BLED Community: a Text Mining Approach

dc.contributor.authorNora Fteimi
dc.contributor.authorMarikka Heikkilä
dc.contributor.authorJukka Heikkilä
dc.contributor.organizationfi=Centre for Collaborative Research (CCR)|en=Centre for Collaborative Research (CCR)|
dc.contributor.organizationfi=tietojärjestelmätiede|en=Information Systems Science|
dc.contributor.organization-code1.2.246.10.2458963.20.70128852004
dc.contributor.organization-code1.2.246.10.2458963.20.87107995810
dc.converis.publication-id47796513
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/47796513
dc.date.accessioned2022-10-28T13:38:29Z
dc.date.available2022-10-28T13:38:29Z
dc.description.abstract<p>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.</p>
dc.format.pagerange499
dc.format.pagerange514
dc.identifier.eisbn978-961-286-362-3
dc.identifier.olddbid183304
dc.identifier.oldhandle10024/166398
dc.identifier.urihttps://www.utupub.fi/handle/11111/40640
dc.identifier.urlhttps://press.um.si/index.php/ump/catalog/book/483
dc.identifier.urnURN:NBN:fi-fe2021042822695
dc.language.isoen
dc.okm.affiliatedauthorHeikkilä, Marikka
dc.okm.affiliatedauthorHeikkilä, Jukka
dc.okm.discipline512 Business and managementen_GB
dc.okm.discipline512 Liiketaloustiedefi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA4 Conference Article
dc.publisher.countrySloveniaen_GB
dc.publisher.countrySloveniafi_FI
dc.publisher.country-codeSI
dc.relation.conferenceBled eConference
dc.relation.ispartofjournalBled eConference
dc.source.identifierhttps://www.utupub.fi/handle/10024/166398
dc.titleTopical Research Cluster of BLED Community: a Text Mining Approach
dc.title.book33rd Bled eConference – Enabling Technology for a Sustainable Society
dc.year.issued2020

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