{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T00:37:15Z","timestamp":1740184635715,"version":"3.37.3"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,3,24]],"date-time":"2024-03-24T00:00:00Z","timestamp":1711238400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,3,24]],"date-time":"2024-03-24T00:00:00Z","timestamp":1711238400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Hum-Cent Intell Syst"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Researchers are keen on finding out about people\u2019s emotions and interests. Personality prediction helps in this issue. Recognizing consumers\u2019 sentiments and desires assists in the development of better recommendation systems and dating applications. Previous personality prediction systems studies had shown personality theories such as Big Five Traits, Three Factor Model, etc. More informative personality model is required because it offers a greater understanding. The target is enabling machines to understand the person more deeply than the previously used models. Enneagram is a distinct personality theory which demonstrates personalities\u2019 motivations, desires and fears. The questionnaire-based exam is the way to inform a person\u2019s Enneagram personality. People are not motivated to complete the exam because it takes time. Enneagram personality prediction system is presented utilizing Enneagram personality model and Twitter text. This does not require any time or effort to predict the personality of the Enneagram. Personality prediction of the Enneagram applies ontology, lexicon and a statistical method. The system\u2019s performance is evaluated using precision, recall, f1-score, and accuracy. The highest personality type recall output is the Enthusiast which is 95%. This is the first technique to predict Enneagram personality from text. The result indicates a good start to predict Enneagram personality.<\/jats:p>","DOI":"10.1007\/s44230-024-00065-3","type":"journal-article","created":{"date-parts":[[2024,3,24]],"date-time":"2024-03-24T15:01:25Z","timestamp":1711292485000},"page":"278-285","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Ontology-Based Enneagram Personality Prediction System"],"prefix":"10.1007","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0690-3839","authenticated-orcid":false,"given":"Esraa","family":"Abdelhamid","sequence":"first","affiliation":[]},{"given":"Sally","family":"Ismail","sequence":"additional","affiliation":[]},{"given":"Mostafa","family":"Aref","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,24]]},"reference":[{"issue":"3","key":"65_CR1","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1007\/s10994-013-5415-y","volume":"95","author":"M Kosinski","year":"2014","unstructured":"Kosinski M, Bachrach Y, Kohli P, Stillwell D, Graepel T. Manifestations of user personality in website choice and behaviour on online social networks. Mach Learn. 2014;95(3):357\u201380.","journal-title":"Mach Learn"},{"issue":"1","key":"65_CR2","first-page":"1","volume":"1","author":"B Agarwal","year":"2014","unstructured":"Agarwal B. Personality detection from text: a review. Int J Comput Syst. 2014;1(1):1\u20134.","journal-title":"Int J Comput Syst."},{"issue":"2","key":"65_CR3","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/s11257-016-9171-0","volume":"26","author":"G Farnadi","year":"2016","unstructured":"Farnadi G, Sitaraman G, Sushmita S, Celli F, Kosinski M, Stillwell D, et al. Computational personality recognition in social media. User Model User-Adap Inter. 2016;26(2):109\u201342.","journal-title":"User Model User-Adap Inter"},{"key":"65_CR4","unstructured":"Sulea OM, Dichiu D. Automatic profiling of Twitter users based on their tweets. Working Notes Papers of the CLEF. 2015."},{"key":"65_CR5","volume-title":"The wisdom of the Enneagram: the complete guide to psychological and spiritual growth for the nine personality types","author":"DR Riso","year":"1999","unstructured":"Riso DR, Hudson R. The wisdom of the Enneagram: the complete guide to psychological and spiritual growth for the nine personality types. New York: Bantam; 1999."},{"issue":"1","key":"65_CR6","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1002\/j.2161-1939.2010.tb00084.x","volume":"49","author":"AM Bland","year":"2010","unstructured":"Bland AM. The Enneagram: a review of the empirical and transformational literature. J Human Counsel Educ Dev. 2010;49(1):16\u201331.","journal-title":"J Human Counsel Educ Dev."},{"issue":"4","key":"65_CR7","first-page":"24","volume":"8","author":"A Demir","year":"2020","unstructured":"Demir A, Rakhmanov O, Tastan K, Dane S, Akturk Z. Development and validation of the Nile personality assessment tool based on enneagram. J Res Med Dental Sci. 2020;8(4):24\u201332.","journal-title":"J Res Med Dental Sci."},{"key":"65_CR8","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1176\/appi.ajp-rj.2020.150301","volume":"15","author":"M Alexander","year":"2020","unstructured":"Alexander M, Schnipke B. The Enneagram: a primer for psychiatry residents. Am J Psychiatry Residents\u2019 J. 2020;15:2\u20135.","journal-title":"Am J Psychiatry Residents\u2019 J"},{"issue":"1","key":"65_CR9","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1007\/s10591-018-9471-0","volume":"41","author":"M Matise","year":"2019","unstructured":"Matise M. The Enneagram: an enhancement to family therapy. Contemp Fam Ther. 2019;41(1):68\u201378.","journal-title":"Contemp Fam Ther"},{"issue":"2","key":"65_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3070645","volume":"12","author":"V Kaushal","year":"2018","unstructured":"Kaushal V, Patwardhan M. Emerging trends in personality identification using online social networks\u2014a literature survey. ACM Trans Knowl Discov Data (TKDD). 2018;12(2):1\u201330.","journal-title":"ACM Trans Knowl Discov Data (TKDD)."},{"issue":"6","key":"65_CR11","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1109\/MIS.2017.4531228","volume":"32","author":"E Cambria","year":"2017","unstructured":"Cambria E, Poria S, Gelbukh A, Thelwall M. Sentiment analysis is a big suitcase. IEEE Intell Syst. 2017;32(6):74\u201380.","journal-title":"IEEE Intell Syst"},{"key":"65_CR12","doi-asserted-by":"crossref","unstructured":"Abdelhamid E, Ismail S, Aref M. Enneaontology: A proposed Enneagram ontology. In: 2nd International Conference on Ubiquitous Computing and Intelligent Information Systems. Singapore: Springer; 2022. p. 559\u2013567.","DOI":"10.1007\/978-981-19-2541-2_46"},{"key":"65_CR13","doi-asserted-by":"crossref","unstructured":"Abdalla\u00a0Abdelhamid E, Ismail S, Aref M. Enneaontology: Toward an enneagram personality detection. In: Proceedings of Third International Conference on Advances in Computer Engineering and Communication Systems, Springer, Singapore; 2022.","DOI":"10.1007\/978-981-19-9228-5_1"},{"key":"65_CR14","unstructured":"Thesaurus.: Thesaurus English Lexicon. https:\/\/www.thesaurus.com\/."},{"issue":"1","key":"65_CR15","first-page":"18","volume":"23","author":"E Abdelhamid","year":"2023","unstructured":"Abdelhamid E, Ismail S, Aref M. Architecture for personality detection using enneagram knowledge: case study. Int J Intell Comput Inform Sci. 2023;23(1):18\u201328.","journal-title":"Int J Intell Comput Inform Sci."},{"key":"65_CR16","first-page":"2088","volume":"13","author":"E Abdelhamid","year":"2023","unstructured":"Abdelhamid E, Ismail S, Aref M. Approach for Enneagram personality detection for twitter text: a case study. Int J Electr Comp Eng. 2023;13:2088\u20138708.","journal-title":"Int J Electr Comp Eng"},{"key":"65_CR17","doi-asserted-by":"crossref","unstructured":"Yang T, Deng J, Quan X, Wang Q. Orders are unwanted: dynamic deep graph convolutional network for personality detection. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol.\u00a037; 2023. p. 13896\u201313904.","DOI":"10.1609\/aaai.v37i11.26627"},{"key":"65_CR18","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1016\/j.future.2021.12.014","volume":"130","author":"M Gjurkovi\u0107","year":"2022","unstructured":"Gjurkovi\u0107 M, Vukojevi\u0107 I, \u0160najder J. SIMPA: statement-to-item matching personality assessment from text. Future Gener Comput Syst. 2022;130:114\u201327.","journal-title":"Future Gener Comput Syst."},{"key":"65_CR19","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1016\/j.ins.2022.03.038","volume":"596","author":"L Zhou","year":"2022","unstructured":"Zhou L, Zhang Z, Zhao L, Yang P. Attention-based BiLSTM models for personality recognition from user-generated content. Inf Sci. 2022;596:460\u201371.","journal-title":"Inf Sci"},{"key":"65_CR20","doi-asserted-by":"crossref","unstructured":"Alamsyah A, Rachman MF, Hudaya CS, Putra RP, Rifkyano AI, Nurwianti F. A progress on the personality measurement model using ontology based on social media text. In: 2019 International Conference on Information Management and Technology (ICIMTech), IEEE. vol.\u00a01; 2019. p. 581\u2013586.","DOI":"10.1109\/ICIMTech.2019.8843817"},{"issue":"3","key":"65_CR21","doi-asserted-by":"publisher","first-page":"100","DOI":"10.25046\/aj050313","volume":"5","author":"A Alamsyah","year":"2020","unstructured":"Alamsyah A, Widiyanesti S, Putra RD, Sari PK. Personality measurement design for ontology based platform using social media text. Adv Sci Technol Eng Syst. 2020;5(3):100\u20137.","journal-title":"Adv Sci Technol Eng Syst."},{"issue":"10","key":"65_CR22","doi-asserted-by":"publisher","first-page":"413","DOI":"10.3390\/info12100413","volume":"12","author":"A Alamsyah","year":"2021","unstructured":"Alamsyah A, Dudija N, Widiyanesti S. New approach of measuring human personality traits using ontology-based model from social media data. Information. 2021;12(10):413.","journal-title":"Information."},{"key":"65_CR23","unstructured":"Ong V, Rahmanto AD, Williem, Suhartono D. Exploring personality prediction from text on social media: a literature review. Internetworking Indonesia. 2017;9(1):65\u201370."},{"key":"65_CR24","unstructured":"Noy NF, McGuinness DL, et\u00a0al.: Ontology development 101: a guide to creating your first ontology. Stanford knowledge systems laboratory technical report KSL-01-05."},{"key":"65_CR25","unstructured":"Institute E.: Official Reformer Enneagram. https:\/\/www.enneagraminstitute.com\/type-1."},{"key":"65_CR26","unstructured":"Institute E.: Official Helper Enneagram. https:\/\/www.enneagraminstitute.com\/type-2."},{"key":"65_CR27","unstructured":"Institute E.: Official Achiever Enneagram. https:\/\/www.enneagraminstitute.com\/type-3."},{"key":"65_CR28","unstructured":"Institute E.: Official Individualist Enneagram. https:\/\/www.enneagraminstitute.com\/type-4."},{"key":"65_CR29","unstructured":"Institute E.: Official Investigator Enneagram. https:\/\/www.enneagraminstitute.com\/type-5."},{"key":"65_CR30","unstructured":"Institute E.: Official Loyalist Enneagram. https:\/\/www.enneagraminstitute.com\/type-6."},{"key":"65_CR31","unstructured":"Institute E.: Official Enthusiast Enneagram. https:\/\/www.enneagraminstitute.com\/type-7."},{"key":"65_CR32","unstructured":"Institute E.: Official Challenger Enneagram. https:\/\/www.enneagraminstitute.com\/type-8."},{"key":"65_CR33","unstructured":"Institute E.: Official Peacemaker Enneagram. https:\/\/www.enneagraminstitute.com\/type-9."}],"container-title":["Human-Centric Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44230-024-00065-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44230-024-00065-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44230-024-00065-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T07:32:58Z","timestamp":1717572778000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44230-024-00065-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,24]]},"references-count":33,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,6]]}},"alternative-id":["65"],"URL":"https:\/\/doi.org\/10.1007\/s44230-024-00065-3","relation":{},"ISSN":["2667-1336"],"issn-type":[{"type":"electronic","value":"2667-1336"}],"subject":[],"published":{"date-parts":[[2024,3,24]]},"assertion":[{"value":"18 September 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 February 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not Applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Not Applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not Applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed Consent"}}]}}