Enneaontology: A Proposed Enneagram Ontology

Abdelhamid, Esraa; Ismail, Sally; Aref, Mostafa

doi:10.1007/978-981-19-2541-2_46

Cited by 3 publications

(5 citation statements)

References 12 publications

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“…Tweets are selected as input to the personality detection approach. The approach utilizes both the Enneagram ontology [19], [20] and the English Lexicon [18]. Enneagram ontology represents Enneagram knowledge.…”

Section: Methodsmentioning

confidence: 99%

“…Feature selection is to pick the personalities' relevant features. This stage is performed using the saurus English lexicon [18] and Enneagram ontology [19], [20] The personality detection phase uses a statistical technique to calculate the personality's probability distribution for each one. The largest probability percentage is the detected personality [21].…”

Section: Introductionmentioning

confidence: 99%

“…Feature selection is vital to pick the important features. The Enneagram ontology [19], [20] and the thesaurus English lexicon [18] are both used in word-based feature selection. Ontology supplies knowledge of a domain [32].…”

mentioning

confidence: 99%

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Approach for Enneagram personality detection for Twitter text: a case study

Abdelhamid,

Ismail,

Aref

2023

IJECE

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Understanding people’s emotions and orientations attracts researchers nowadays. Current personality detection research concentrates on models such as the big five model, the three-factor model. The Enneagram is deeper than these models for providing a comprehensive view. This theory is a unique personality model because it illustrates what drives human behavior. This recognition helps in building smarter recommendation systems and intelligent educational systems. Enneagram personalities are realized through a long questionnaire-based test. People are not concerned about doing a test because it is time-consuming. A proposed case study employs Twitter’s text to detect Enneagram personality because it requires no time or effort. The proposed case study is based on an approach that uses a combination of ontology, lexicon, and statistical technique. This proposed case study uses the biography description text and 40 tweets of a Twitter profile text. The highest probability percentage is peacemaker personality which is 15.58%. This result means that the identified personality is the peacemaker. The outcome is equivalent to the determination of the Enneagram’s specialized people. This result promises more positive outcomes. This is the first automated approach to determine the Enneagram from text.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Approach for Enneagram personality detection for Twitter text: a case study

Abdelhamid,

Ismail,

Aref

2023

IJECE

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“…Feature selection is utilized in order to pick meaningful features. This step is done by using Enneagram ontology [12,13] and thesaurus English lexicon [14]. The required knowledge of the Enneagram is represented by Enneagram ontology.…”

Section: Design Of Enneagram Personality Predictionmentioning

confidence: 99%

“…Conversion of text to words as features is done in the second step. Feature picking is accomplished using Enneagram ontology [12,13] and English lexicon [14]. Personality prediction which is a statistical method to select highest probability distribution among personalities [15,16].…”

Section: Introductionmentioning

confidence: 99%

Ontology-Based Enneagram Personality Prediction System

Abdelhamid,

Ismail,

Aref

2024

Hum-Cent Intell Syst

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Researchers are keen on finding out about people’s emotions and interests. Personality prediction helps in this issue. Recognizing consumers’ 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’ motivations, desires and fears. The questionnaire-based exam is the way to inform a person’s 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’s 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.

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