[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-293002-105":59,"doc-detail-293002-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","explainable-multi-label-classification-of-mbti-types","Explainable Multi-Label Classification of MBTI Types","","Study aims to determine the most effective machine learning model for classifying Myers-Briggs Type Indicator (MBTI) types from Reddit posts using a multi-label framework with the Binary Relevance method. An Explainable Artificial Intelligence (XAI) approach is applied to improve transparency and interpretability through glass-box learning models. The work compares k-Nearest Neighbours, Multinomial Naive Bayes, and Logistic Regression, reporting best performance patterns under specific class-exclusion and dataset-size conditions.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/explainable-multi-label-classification-of-mbti-types/293002/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/explainable-multi-label-classification-of-mbti-types/293002.png","ImageObject",300,407,{"name":92,"@type":93},"Adam","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":52},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What classification approach is used to predict MBTI types from Reddit posts?","Question",{"text":112,"@type":113},"The study uses multi-label classification with the Binary Relevance method to predict MBTI types based on post text.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which glass-box machine learning models are compared in the study?",{"text":117,"@type":113},"The models selected for glass-box learning are k-Nearest Neighbours, Multinomial Naive Bayes, and Logistic Regression.",{"name":119,"@type":110,"acceptedAnswer":120},"How do model performances change when excluding certain classes or using data size constraints?",{"text":121,"@type":113},"Multinomial Naive Bayes and k-Nearest Neighbour perform better when classes with Observer (S) traits are excluded, while Logistic Regression achieves best results when all classes have more than 550 entries.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},293002,1789658533,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":52,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":129,"read_time":144,"preview_page_count":4},1374404737137,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Explainable Multi-Label Classification of MBTI Types  \nSiana Kong Marina Sokolova  \nEECS, University of Ottawa EECS and SEPH, University of Ottawa  \n[skong005@uottawa.ca](skong005@uottawa.ca) [sokolova@uottawa.ca](sokolova@uottawa.ca)  \nAbstract  \nIn this study, we aim to identify the most effective machine learning model for accurately classifying Myers-Briggs Type Indicator (MBTI) types from Reddit posts and a Kaggle data set. We apply multi-label classification using the Binary Relevance method. We use Explainable Artificial Intelligence (XAI) approach to highlight the transparency and understandability of the process and result. To achieve this, we experiment with glass-box learning models, i.e. models designed for simplicity, transparency, and interpretability. We selected k-Nearest Neighbours, Multinomial Naive Bayes, and Logistic Regression for the glass-box models. We show that Multinomial Naïve Bayes and k-Nearest Neighbour perform better if classes with Observer (S) traits are excluded, whereas Logistic Regression obtains its best results when all classes have > 550 entries.  \n1. Introduction  \nAn individual’s personality refers to their unique set of traits and behaviour, as well as the patterns of thinking and feeling (Cherry, 2023) . Although everyone’s personality is unique to themselves, there exist various frameworks and models to categorize personalities into distinct types. By identifying common patterns of traits, behaviors, and characteristics, these tools categorize personalities to group people with similar personalities together. This categorization can help people to understand themselves better, as well as other people by learning about different personality types. Myers-Briggs Type Indicator (MBTI) is an indicator widely used today. MBTI was developed by Katharine Cook Briggs and Isabel Briggs Myers, inspired by Carl Jung’s theory of psychological types. It assigns personalities into Energy [Extraverted(E) / Introverted(I)], Mind [Intuitive(N) / Observant(S)], Nature [Feeling(F) / Thinking(T)], and Tactics [Judging(J) / Prospecting(P)], where the different combinations of these four letters makeup different personality types (NERIS Analytics Limited, 2013) .  \nWe hypothesize that people with similar MBTI traits are likely to show similar behavior and interests online. Therefore, our main assumption is that MBTI type of individuals can be predicted based on the posts they make online. To test the hypothesis, we decided to experiment with different machine learning models to find the most fitting model for predicting a person’s MBTI type based on the posts’ text.  \nWe use the posts from each different MBTI type’s subreddits on Reddit to show that people’s personality type influences the way they behave and the topics they discuss in the online world. To make the results easier to understand and interpret, we employ the Explainable Artificial Intelligence (XAI) approach. XAI puts focus on “producing more explainable models, while maintaining a high level of learning performance”(Turek, n.d.) . For prospective end users of AI applications and Machine Learning algorithms, XAI helps to understand the results better, enabling to analyze and compare different outcomes more easily, emphasizes the transparency of the process, which allows us to understand how the results came to be without having to dissect the entire process.  \nWe use glass-box models, one of the most straightforward approaches of XAI. Those are models that are easy to follow, and their decision making processes are straightforward and easy to understand, the key aspect of XAI (Roelenga, 2021) . The key advantages of Glass-box models include:  \n➢ Transparency: able to observe exactly how the inputs results in such outputs  \n➢ Simplicity: use of straightforward methods that are easy to follow  \n➢ Interpretability: easy to interpret why and how certain decisions are made For our learning, we selected Multinomial Naive Bayes, k-Nearest Neighbour ","cbCailicxOqPbr7A","https://ap.wps.com/l/cbCailicxOqPbr7A","pdf",312149,22,"English","# Abstract\n# Introduction\n# Myers-Briggs Type Indicator\n# Methodology and Glass-Box Models\n# Results and Evaluation Metrics","[{\"question\":\"What classification approach is used to predict MBTI types from Reddit posts?\",\"answer\":\"The study uses multi-label classification with the Binary Relevance method to predict MBTI types based on post text.\"},{\"question\":\"Which glass-box machine learning models are compared in the study?\",\"answer\":\"The models selected for glass-box learning are k-Nearest Neighbours, Multinomial Naive Bayes, and Logistic Regression.\"},{\"question\":\"How do model performances change when excluding certain classes or using data size constraints?\",\"answer\":\"Multinomial Naive Bayes and k-Nearest Neighbour perform better when classes with Observer (S) traits are excluded, while Logistic Regression achieves best results when all classes have more than 550 entries.\"}]","Explainable Multi-Label Classification of MBTI Types | PDF",55]