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Authors: Marco Nardello 1 ; Charles Møller 1 and John Gøtze 2

Affiliations: 1 Aalborg University, Denmark ; 2 IT University of Copenhagen and QualiWare aps, Denmark

Keyword(s): Enterprise Architecture, Topic Modelling, Content Analysis, Research Theme, Future Research, Machine Learning, Latent Dirichlet Allocation.

Abstract: The next 3 years will be more important than the last 50 due to the digital transformation across industries. Enterprise Architecture (EA), the discipline that should lead enterprise responses to disruptive forces, is far from ready to drive the next wave of change. The state of the art in the discipline is not clear and the understanding among researchers and practitioners is not aligned. To address these problems, we developed a topic model to help structure the field and enable EA to evolve coherently. In this preliminary study, we present the 360 identified topics in EA literature and their evolution over time. Our study supports and combines the findings from previous research and provides both a deeper analysis and more detailed findings.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Nardello, M.; Møller, C. and Gøtze, J. (2018). Understanding Enterprise Architecture with Topic Modeling - Preliminary Research based on Journal Articles. In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-298-1; ISSN 2184-4992, SciTePress, pages 640-648. DOI: 10.5220/0006693106400648

@conference{iceis18,
author={Marco Nardello. and Charles Møller. and John Gøtze.},
title={Understanding Enterprise Architecture with Topic Modeling - Preliminary Research based on Journal Articles},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2018},
pages={640-648},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006693106400648},
isbn={978-989-758-298-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Understanding Enterprise Architecture with Topic Modeling - Preliminary Research based on Journal Articles
SN - 978-989-758-298-1
IS - 2184-4992
AU - Nardello, M.
AU - Møller, C.
AU - Gøtze, J.
PY - 2018
SP - 640
EP - 648
DO - 10.5220/0006693106400648
PB - SciTePress