Abstract
Personality prediction catches research attention nowadays. In social media, attracting more users means getting more advertisements. Enneagram is a personality model which is used by psychiatrists. Enneagram is utilized to understand patients’ personalities. This knowledge helps them to give the right support. The current method to realize Enneagram is questionnaire based. Humans feel boring to do long questionnaire. Enneagram personality detection system is required. There is not any knowledge representation for the Enneagram. Enneaontology provides an ontology for Enneagram. Enneaontology contains seven classes and nine objects. These classes are Enneagram, key motivation, fear, feature, desire, problem and best classes. These objects are reformer, helper, achiever, individualist, investigator, loyalist, enthusiast, challenger and peacemaker. Enneaontology is designed relative to METHONTOLOGY principles. Enneaontology is evaluated with Enneagram personality detection application. The promising results verify Enneaontology. Enneaontology is the first Enneagram ontology.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
E. Abdelhamid, S. Ismail,, M. Aref, Enneaontology: a proposed enneagram ontology, in 2nd International Conference on Ubiquitous Computing and Intelligent Information Systems. Smart Innovation, Systems and Technologies (Springer, 2022), pp. 541–549
A. Alamsyah, M.F. Rachman, C.S. Hudaya, R.P. Putra, A.I. Rifkyano, F. Nurwianti, A progress on the personality measurement model using ontology based on social media text, in 2019 International Conference on Information Management and Technology (ICIMTech), vol. 1 (IEEE, 2019), pp. 581–586
A. Alamsyah, S. Widiyanesti, R.D. Putra, P.K. Sari, Personality measurement design for ontology based platform using social media text. Adv. Sci. Technol. Eng. Syst. 5(3), 100–107 (2020)
M. Alexander, B. Schnipke, The enneagram: a primer for psychiatry residents. Am. J. Psychiatry Res. J. (2020)
R. Baron, E. Wagele, The Enneagram Made Easy: Discover the 9 Types of People (Harper Collins, 2009)
T. Berners-Lee, J. Hendler, O. Lassila, The semantic web. Sci. Am. 284(5), 34–43 (2001)
A.M. Bland, The enneagram: a review of the empirical and transformational literature. J. Humanist. Couns. Educ. Dev. 49(1), 16–31 (2010)
J. Brank, M. Grobelnik, D. Mladenic, A survey of ontology evaluation techniques, in Proceedings of the Conference on Data Mining and Data Warehouses (SiKDD 2005) (Citeseer, Ljubljana, Slovenia, 2005), pp. 166–170
A. Demir, O. Rakhmanov, K. Tastan, S. Dane, Z. Akturk, Development and validation of the nile personality assessment tool based on enneagram. J. Res. Med. Dent. Sci. 8(4), 24–32 (2020)
Enneagram official institute. https://www.enneagraminstitute.com/
Enneagram types description. https://www.enneagraminstitute.com/type-descriptions
G. Farnadi, G. Sitaraman, S. Sushmita, F. Celli, M. Kosinski, D. Stillwell, S. Davalos, M.F. Moens, M. De Cock, Computational personality recognition in social media. User Model. User Adap. Inter. 26(2), 109–142 (2016)
M. Fernandez, A. Gomez-Perez, N. Juristo, Methontology: from ontological art towards ontological engineering, in Proceedings of the AAAI97 Spring Symposium Series on Ontological Engineering (Stanford, USA, 1997), pp. 33–40
Y.M.F. Geovanni, A. Alamsyah, N. Dudija et al., Identifying personality of the new job applicants using the ontology model on twitter data, in 2021 2nd International Conference on ICT for Rural Development (IC-ICTRuDev) (IEEE, 2021), pp. 1–5
A. Gómez-Pérez, M. Fernández-López, O. Corcho, Ontological Engineering: With Examples from the Areas of Knowledge Management, e-Commerce and the Semantic Web (Springer Science & Business Media, 2006)
M. Horridge, H. Knublauch, A. Rector, R. Stevens, C. Wroe, A practical guide to building owl ontologies using the protégé-owl plugin and co-ode tools edition 1.0. University of Manchester (2004)
V. Kaushal, M. Patwardhan, Emerging trends in personality identification using online social networks—a literature survey. ACM Trans. Knowl. Discov. Data (TKDD) 12(2), 1–30 (2018)
M. Matise, The enneagram: an enhancement to family therapy. Contemp. Fam. Ther. 41(1), 68–78 (2019)
N.F. Noy, D.L. McGuinness et al.: Ontology Development 101: A Guide to Creating Your First Ontology (2001)
V. Ong, A.D. Rahmanto, W. Williem, D. Suhartono, Exploring personality prediction from text on social media: a literature review. Internetworking Indones. 9(1), 65–70 (2017)
J. Raad, C. Cruz, A survey on ontology evaluation methods, in Proceedings of the International Conference on Knowledge Engineering and Ontology Development, Part of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (2015)
D.R. Riso, R. Hudson, The Wisdom of the Enneagram: The Complete Guide to Psychological and Spiritual Growth for the Nine Personality Types (Bantam, 1999)
K. Sekandar, A quality measure for automatic ontology evaluation and improvement. Master’s thesis (2018)
D. Sewwandi, K., Perera, S., Sandaruwan, O., Lakchani, A., Nugaliyadde, S., Thelijjagoda, Linguistic features based personality recognition using social media data, in 2017 6th National Conference on Technology and Management (NCTM) (IEEE, 2017), pp. 63–68
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Abdelhamid, E.A., Ismail, S., Aref, M. (2023). Enneaontology: Toward an Enneagram Personality Detection. In: Reddy, A.B., Nagini, S., Balas, V.E., Raju, K.S. (eds) Proceedings of Third International Conference on Advances in Computer Engineering and Communication Systems. Lecture Notes in Networks and Systems, vol 612. Springer, Singapore. https://doi.org/10.1007/978-981-19-9228-5_1
Download citation
DOI: https://doi.org/10.1007/978-981-19-9228-5_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-9227-8
Online ISBN: 978-981-19-9228-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)