[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-293553-105":59,"doc-detail-293553-en":131},{"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":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","an-analysis-of-different-machine-learning-algorithms-for-personality-type-predictions-based-on-social-media-posts","An Analysis of Different Machine Learning Algorithms for Personality Type Predictions Based on Social Media Posts","","This study evaluates machine learning approaches for MBTI personality type prediction from users’ social media posts, focusing on Naive Bayes (NB), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost). Comparative analysis across modeling performance indicates no clear dependence of accuracy on the training method, with all models producing closely related results. XGBoost models show the highest average accuracy, and the best outcome is achieved with well-tuned hyperparameters. Additional discussion considers how data distribution affects model performance and highlights potential value for advancing analytical psychology.",{"@graph":69,"@context":123},[70,84,106],{"@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/an-analysis-of-different-machine-learning-algorithms-for-personality-type-predictions-based-on-social-media-posts/293553/",{"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/an-analysis-of-different-machine-learning-algorithms-for-personality-type-predictions-based-on-social-media-posts/293553.png","ImageObject",300,407,{"name":92,"@type":93},"Finn","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"Which algorithms are compared for MBTI personality type prediction?","Question",{"text":113,"@type":114},"The study compares Naive Bayes (NB), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) using social media posts as input.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"What conclusion does the study draw about accuracy across training approaches?",{"text":118,"@type":114},"Results show no evident correlation between model accuracy and the training method; each model’s predictive capability varies, but the outcomes are very close overall.",{"name":120,"@type":111,"acceptedAnswer":121},"How does XGBoost perform relative to NB and SVM?",{"text":122,"@type":114},"Models trained on XGBoost achieve the highest accuracy on average, and the best performance comes from an XGBoost model with well-tuned hyperparameters.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},293553,1789665506,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":29,"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":130,"read_time":144,"preview_page_count":4},34359740700684,"https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487","# An Analysis of Different Machine Learning Algorithms forPersonality Type Predictions Based on Social Media Posts\n\nRuiwen Yu  \nUniversity High School,Irvine,California,92603,U.S.A.  \nPersonality Type Predictions,MBTI,Machine Learning.  \nAbstract:In the digital era,people have increasingly used social media as a platform to communicate with each otherand express feelings.Researchers have vast data to predict users'personalities,who play various practicalroles in real life.This paper focuses on MBTI personality trait prediction based on users'social media posts.Comparisons and Analyses are made between the three most common methods of personality prediction,including Naive Bayes (NB),Support Vector Machine(SVM),and Extreme Gradient Boosting(XGBoost),to find out the most effective one.Results show no evident correlation between the accuracy of the modelsand the training method;each model's capability to predict varies.Models trained on XGBoost have thehighest accuracy on average,althoughallthree outcomes are incredibly close.One model trained on XGBoostwith well-tuned hyperparameters obtained the best performance.Further analyses show other factors.Forexample,data distribution also influences the model's performance in some ways.  \npersonality type can help users learn more aboutthemselves online,and increase self-awareness.Mostimportantly,further machine learning research onpersonality prediction has the potential to helpadvance analytic psychology and personality science(W.Bleidorn et al.,2018).  \n## 1 INTRODUCTION\n\nPersonality is the combination of characteristics orqualities that form an individual's distinctivecharacter.It originated from the Latin word persona,which means mask or a character played by the actor.Right now,a person's personality represents thecombination of characteristics or qualities that form anindividual's distinctive character.It can be the waythey perceive the world,the way they make decisions,their values,beliefs,and goals of life.  \nThis research compares and analyzes theperformance of different machine-learning methods.Comparisons are made on multiple angles.The goal isto find the most effective and accurate algorithm forpersonality prediction.  \nResearchers increasingly gain interest inpredicting users'personality types.Personalityrecognition is very helpful and important in the agewhen social media has become a major place forpeople to communicate and share their thoughts.Itallows the recommendation system to work moreeffectively,recommending the appropriate content totargeted groups of people who find that interest them,therefore improving the user experience(G.Ryan etal.,2023).In addition,it enables both sides to knowmore about each other's thoughts and preferences insome scenarios that require communication.Thismutual understanding is helpful to avoidmisunderstandings and make the communicationmore productive,therefore achieving the goals withminimum efforts.  Moreover,knowing one's  \n## 2 RELATED WORKS\n\nThere are three main aspects of machine learning inpersonality prediction(C.Stachl et al.,2020).The firstone is customized recommendation systems in socialmedia,matching content to people.It makes sure thecontents recommended are tailored to eachindividual's preferences.The second would bepersonal evaluations that answer methodologicalquestions,including predictions of life outcomes,taskperformance,etc.The third one predicts the actualpersonality traits of people.It can be based on variousmeans,like facial features,handwriting,signatures,and more(K.Ilmini and T.G.I.Fernando,2016)-(K.  \n386  \nIlmini and T.G.I.Fernando,2020).However,researchers commonly use digital footprints like postson social media to train models that predict user traits.  \nThere are two popular personality identifiers:BigFive and MBTI.Multiple researches have beenconducted on both of them.Big Five refers toOpenness,   (Conscientiousness,   Extraversion,Agreeableness,and Neuroticism.This study willmainly focus on MBTI,one of ","cbCailVQ3RdMLzRR","https://ap.wps.com/l/cbCailVQ3RdMLzRR","pdf",454279,"English","# 1 INTRODUCTION\n# 2 RELATED WORKS\n# 3 CASE ANALYSIS","[{\"question\":\"Which algorithms are compared for MBTI personality type prediction?\",\"answer\":\"The study compares Naive Bayes (NB), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) using social media posts as input.\"},{\"question\":\"What conclusion does the study draw about accuracy across training approaches?\",\"answer\":\"Results show no evident correlation between model accuracy and the training method; each model’s predictive capability varies, but the outcomes are very close overall.\"},{\"question\":\"How does XGBoost perform relative to NB and SVM?\",\"answer\":\"Models trained on XGBoost achieve the highest accuracy on average, and the best performance comes from an XGBoost model with well-tuned hyperparameters.\"}]","An Analysis of Different Machine Learning Algorithms for Personality Type Predictions Based on Social Media Posts | PDF",15]