Using the Myers-Briggs Type Indicator (MBTI) for Modeling Multiagent Systems

The formation of high-performance teams has been a constant challenge for organizations, which despite considering human capital as one of the most important resources, it still lacks the means to allow them to have a better understanding of several factors that influence the formation of these teams. In this sense, studies also demonstrate that teamwork has a significant impact on the results presented by organizations, in which human behavior is highlighted as one of the main aspects to be considered in the building of work teams. The Myers-Briggs Type Indicator seeks to classify the behavioral preferences of individuals around eight characteristics, which grouped as dichotomies, describe different psychological types. With it, researchers have sought to expand the ability to understand the human factor, using strategies with multiagent systems that, through experiments and simulations, using computer resources, enable the development of artificial agents that simulate human actions. In this work, we present an overview of the research approaches that use MBTI to model agents, aiming at providing a better knowledge of human behavior. Additionally, we make a preliminary discussion of how these results could be explored in order to advance the studies of psychological factors' influence in organizations' work teams formation.

Prediction Of Myers-Briggs Type Indicator Personality Using Long Short-Term Memory

Personality is defined as the mix of features and qualities that make up an individual's particular character, including thoughts, feelings, and behaviors. With the rapid development of technology, personality computing is becoming a popular research field by providing users with personalization. Many researchers have used social media data to automatically predict personality. This research uses a public dataset from Kaggle, namely the Myers-Briggs Personality Type Dataset. The purpose of this study is to predict the accuracy and F1-score values so that the performance for predicting and classifying Myers–Briggs Type Indicator (MBTI) personality can work optimally by using attributes from the MBTI dataset, namely posts and types. Predictive accuracy analysis was carried out using the Long Short-Term Memory (LSTM) algorithm with random oversampling technique with the Imblearn library for MBTI personality type prediction and comparing the performance of the method proposed in this study with other popular machine learning algorithms. Experiments show that the LSTM model using the RMSprop optimizer and learning speed of 10-3 provides higher performance in terms of accuracy while for the F1-score the LSTM model using the RMSprop Optimizer and learning speed of 10-2 gives a higher value than the proposed machine learning algorithm so that the model MBTI dataset using LSTM with random oversampling can help in identifying the MBTI personality type.

Building an Entrepreneurial Spirit Based on Model, Brain Color and Myers Briggs Type Indicator (MBTI)

One of the characteristics of an entrepreneur is that his thoughts and insights are oriented towards Action rather than just dreaming, wishing and talking. An entrepreneur always faces risk with uncertainty and limitations in every problem he faces. If we only speak words and do not take action, all opportunities that exist will turn into disasters and calamities in our lives. A drafter or theorist, works with data and is rarely in the field. On the other hand, an entrepreneur spends 95% of his time in the field with his employees, suppliers and customers. Because working with data, in order to be valid and scientific, a drafter must be accustomed to testing the data, building a model and doing validation. What will be a problem if a drafter does not master the situation and information in the field and can become doubtful about his decision so that he tends to repeat the cycle again. Namely collecting data that causes him to be spindly and more oriented to the mind than Action. On the other hand, an Action-oriented person is a person who has a high level of effectiveness. To study the characteristics of an Action-oriented person using the model of an effective person

Personality Types and L2 Reading: correlation between University Students MBTI Profiles and Reading Proficiency

Personality types have a considerable impact on our understanding of the outer world, perception and energy. Personality influence on language learning and proficiency, however, is controversial. This study demonstrates the relationship between the Myers-Briggs Type Indicator (MBTI) profiles and L2 reading proficiency of L1 Arab undergraduates. First, learners' reading proficiency levels were associated with their Introversion/Extraversion preferences. Then, function pairs of both introverts and extraverts that contributes to the highest score of L2 reading proficiency were determined. As most reading tests are based on choice, it is very logical to consider the MBTI function pairs as they represent the mental functions used for decision-making and information gathering. Fifty (50) Arab male students from the College of Business Administration (Saudi Arabia) were randomly selected. Two instruments were used to collect data; MBTI as a personality instrument, and TOEIC Bridge as a reading test. Findings showed a lack of statistically significant relationship between Introversion/Extraversion and L2 reading proficiency. Yet, Intuitive personalities (NT/NF) preferences achieved higher scores in the TOEIC Bridge compared to their counterparts of the Sensing personalities (ST/SF). Personality types have undoubted influence on our lifestyle and attitudes. Yet, considering personality as a weighty factor in language learning and proficiency is still debatable.

Personality of a Good Language Learner: a Case Study in EFL Context

This case study aims to explore how the personality traits of a good language learner contributed to her success in language learning. Using a case study design, this study involved one student who met the criteria of a good language learner who became a champion of English competitions. This study used the Myers-Briggs Type Indicator personality test and semi-structured interviews to collect the data. The study showed that Meta's extrovert personality was described as talkative, confident, enthusiastic, and assertive. She understood a problem by talking about it and heard others' ideas in solving problems. As a sensing personality, she was objective and made decisions based on logic and facts to decide both sides. As a thinking person, she always worked with plans, and in making plans, she analyzed the pros and cons. She was objective and consistent in doing what she had planned. Her judging personality described how she dealt with their outer world. She had a decided lifestyle that had helped her achieve her goals in language learning by planning her language learning activities.

Personality in information systems professions: identifying archetypal professions with suitable traits and candidates' ability to fake-good these traits

PurposeThe importance of information systems (IS) professions is increasing. As personality–job fit theory claims, employees must have suitable personality traits for particular IS professions. However, candidates can try to fake-good on personality tests towards the desired personality type. Thus, the purpose of this study is to identify archetypal IS professions, their associated personality types and examine the reliability of the Myers–Briggs Type Indicator (MBTI) personality test in IS recruitment decisions.Design/methodology/approachThe authors reviewed academic literature related to IS professions to identify job archetypes and personality traits for IS professions. Then, the authors conducted an experiment with 452 participants to investigate whether candidates can fake-good on personality tests when being tested for a particular IS profession.FindingsThe identified job archetypes were IS project manager, IS marketing specialist, IS consultant, IS security specialist, data scientist and business process analyst. The experimental results show that the participants were not able to fake-good considerably regarding their personality traits for a particular archetype.Research limitations/implicationsThe taxonomy of IS professions should be validated further. The experiment was executed in an educational organisation and not in a real-life environment. Actual work performance was not measured.Practical implicationsThis study enables a better identification of suitable candidates for a particular IS profession. Personality tests are good indicators of the candidate's true personality type but must be properly interpreted.Originality/valueThis study enhances the existing body of knowledge on IS professions' archetypes, proposes suitable MBTI personality types for each profession and provides experimental support for the appropriateness of using personality tests to identify potentially suitable candidates.

Speech Characteristics as Indicators of Personality Traits

This study examines the relationship between speech characteristics and personality traits by drawing on pseudo-naturalistic conversations and on personality dimensions identified by the Myers–Briggs Type Indicator (MBTI) model which assesses four personality dimensions of introversion-extroversion, sensing-intuiting, thinking-feeling, and judging-perceiving. The speech of 30 participants was recorded and transcribed, after which a number of speech features including pitch, loudness, response time (i.e., how fast one responds to a prompt), speech rate, and discourse markers were extracted and analyzed. Results show that several speech features correspond to different personality dimensions. Specifically, speech rate as measured by words per minute reveals significant differences between judging individuals and perceiving individuals (perceiving individuals speak faster than judging individuals); there is a significant difference in response time for extroverts and introverts (extroverts respond faster); a significant difference is observed in loudness between judging and perceiving individuals (judging individuals are louder). The frequency of discourse markers is significantly higher for intuiting individuals than sensing individuals. The study discusses these findings in further inquiring the relationship between language and personality.

EEG-Based Personality Prediction Using Fast Fourier Transform and DeepLSTM Model

In this paper, a deep long short term memory (DeepLSTM) network to classify personality traits using the electroencephalogram (EEG) signals is implemented. For this research, the Myers–Briggs Type Indicator (MBTI) model for predicting personality is used. There are four groups in MBTI, and each group consists of two traits versus each other; i.e., out of these two traits, every individual will have one personality trait in them. We have collected EEG data using a single NeuroSky MindWave Mobile 2 dry electrode unit. For data collection, 40 Hindi and English video clips were included in a standard database. All clips provoke various emotions, and data collection is focused on these emotions, as the clips include targeted, inductive scenes of personality. Fifty participants engaged in this research and willingly agreed to provide brain signals. We compared the performance of our deep learning DeepLSTM model with other state-of-the-art-based machine learning classifiers such as artificial neural network (ANN), K-nearest neighbors (KNN), LibSVM, and hybrid genetic programming (HGP). The analysis shows that, for the 10-fold partitioning method, the DeepLSTM model surpasses the other state-of-the-art models and offers a maximum classification accuracy of 96.94%. The proposed DeepLSTM model was also applied to the publicly available ASCERTAIN EEG dataset and showed an improvement over the state-of-the-art methods.

Myers-Briggs Type Indicator Personality Types of Ophthalmology Residents

Objective This study attempts to use the Myers-Briggs Type Indicator (MBTI) to analyze personality types among current and recent ophthalmology residents. We aimed to evaluate the prevalence rates of each specific personality type in ophthalmology, and whether these changed by level of training, training program, or fellowship selection. The study aimed to evaluate whether certain personality types are more prevalent in ophthalmology as a unique medical specialty. This can help understand specialty choice and potentially predict trends in specialty selection. Study Design After obtaining institutional review board approval from Howard University Hospital, an electronic version of the MBTI questionnaire, form M, was sent to participants. In addition to the questionnaire, participants responded to four questions inquiring about home program, postgraduate training level, subspecialty interest, and work environment (if applicable). The anonymous responses of the surveys were automatically scored on google forms, and the results were analyzed by using StatView statistical analysis. Setting This study was conducted at Howard University, Georgetown University, George Washington University, University of Texas Medical Branch at Galveston, and Kresge Eye Institute. Participants A total of 66 current residents and recent graduates of five residency programs were involved in this study. Main Outcomes and Measures This study evaluated four-letter personality type from each participant. Results Ophthalmology residents were statistically more likely to be identified in the categories of extroversion (E) than introversion (I) (p = 0.049), thinking (T) than feeling (F) (p = 0.027), and judging (J) than perceiving (P) (p = 0.007), with no statistically significant difference between sensing (S) and intuition (N). ENTP, ESTJ, and ISTJ were the most common personality types, each comprising 13.6% of the sample population. The ratio of J:P was found to increase as training level increased, beginning with postgraduate 2nd year until graduate level. Conclusion Certain personality types are more common among ophthalmology residents in our cohort from five different training programs. It is possible that individual types change over the course of residency training and career. Understanding that these findings exist can be used as a baseline for future research in terms of potential predictors for applicants, of resident knowledge base, and personality changes over the course of one's training.

Predicting judging-perceiving of Myers-Briggs Type Indicator (MBTI) in online social forum

The Myers-Briggs Type Indicator (MBTI) is a well-known personality test that assigns a personality type to a user by using four traits dichotomies. For many years, people have used MBTI as an instrument to develop self-awareness and to guide their personal decisions. Previous researches have good successes in predicting Extraversion-Introversion (E/I), Sensing-Intuition (S/N) and Thinking-Feeling (T/F) dichotomies from textual data but struggled to do so with Judging-Perceiving (J/P) dichotomy. J/P dichotomy in MBTI is a non-separable part of MBTI that have significant inference on human behavior, perception and decision towards their surroundings. It is an assessment on how someone interacts with the world when making decision. This research was set out to evaluate the performance of the individual features and classifiers for J/P dichotomy in personality computing. At the end, data leakage was found in dataset originating from the Personality Forum Café, which was used in recent researches. The results obtained from the previous research on this dataset were suggested to be overly optimistic. Using the same settings, this research managed to outperform previous researches. Five machine learning algorithms were compared, and LightGBM model was recommended for the task of predicting J/P dichotomy in MBTI personality computing.