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Typological MBTI and dimensional Big Five frameworks are evaluated using the Essays and MBTI datasets, employing log-odds ratio with Informative Dirichlet Prior and fine-tuned BERT/RoBERTa transformers. Results show moderate-to-high accuracy, theory-coherent language patterns, and dataset biases.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/text-speaks-louder-insights-into-personality-from-natural-language-processing/293167/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/text-speaks-louder-insights-into-personality-from-natural-language-processing/293167.png","ImageObject",300,407,{"name":42,"@type":43},"Guten tag","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-24","2026-09-17",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",12,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What explainable AI method is central to the study?","Question",{"text":63,"@type":64},"The article uses explainable AI techniques, particularly Integrated Gradients, to scrutinize how NLP models make decisions in personality assessment.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"Which personality frameworks are compared?",{"text":68,"@type":64},"It compares typological models (MBTI) and dimensional models (Big Five) for classifying personality traits from text.",{"name":70,"@type":61,"acceptedAnswer":71},"How are the NLP models trained and evaluated?",{"text":72,"@type":64},"The methodology applies log-odds ratio with an Informative Dirichlet Prior and uses fine-tuned transformer models including BERT and RoBERTa on the Essays and MBTI datasets.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},293167,1789660552,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,111,115,120,123,127],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":112,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":113,"slug":114},8,30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":25,"category_name":129,"show_sort_weight":97,"slug":130},19,"General","general",{"code":4,"msg":82,"data":132},{"doc_id":79,"user_id":133,"nickname":42,"user_avatar":134,"doc_module":4,"category_id":112,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":140,"language":141,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":12,"update_tm":80,"read_time":145,"preview_page_count":4},687212321768,"https://ap-avatar.wpscdn.com/avatar/a0010bdbe886d2fe77?x-image-process=image/resize,m_fixed,w_180,h_180&k=1789897067658708522","PLOS ONE  \nOPEN ACCESS  \nCitation: Saeteros D, Gallardo-Pujol D, Ortiz-Martínez D (2025) Text speaks louder:  \nInsights into personality from natural language processing. PLoS One 20(6): e0323096 .  \n[https://doi.org/10.1371/journal.pone.0323096](https://doi.org/10.1371/journal.pone.0323096)  \nEditor: Vijaya Prakash Rajanala, SR University, INDIA  \nReceived: August 29, 2024  \nAccepted: March 27, 2025  \nPublished: June 18, 2025  \nPeer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: [https://doi.org/10.1371/journal.pone](https://doi.org/10.1371/journal.pone). 0323096  \nCopyright: © 2025 Saeteros et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.  \nData availability statement:  \n[https://osf.io/sgvta/](https://osf.io/sgvta/)  \nRESEARCH ARTICLE  \nText speaks louder: Insights into personality from natural language processing  \nDavid Saeteros1 , David Gallardo-Pujol1,2,3 , Daniel Ortiz-Martínez4 ∗  \n1 Department of Clinical Psychology and Psychobiology, Universitat de Barcelona, Barcelona, Spain, 2 Institut de Neurociències (UBNEURO), Barcelona, Spain, 3 Institute of Complex Systems (UBICS), Barcelona, Spain, 4 Department of Mathematics and Computer Science, Universitat de Barcelona, Barcelona, Spain  \n∗ [daniel.ortiz@ub.edu](daniel.ortiz@ub.edu)  \nAbstract  \nIn recent years, advancements in natural language processing (NLP) have enabled new approaches to personality assessment. This article presents an interdisciplinary investigation that leverages explainable AI techniques, particularly Integrated Gradients, to scrutinize NLP models’ decision-making processes in personality assessment and verify their alignment with established personality theories. We compare the effectiveness of typological (MBTI) and dimensional (Big Five) models, utilizing the Essays and MBTI datasets. Our methodology applies log-odds ratio with Informative Dirichlet Prior (IDP) and fine-tuned transformer-based models (BERT and RoBERTa) to classify personality traits from textual data. Our results demonstrate moderate to high accuracy in personality prediction, with NLP models effectively identifying personality signals in text in line with previous studies. Our findings reveal theory-coherent patterns in language use associated with different personality traits, while highlighting important biases in the MBTI dataset that yielded less robust results. The study underscores the potential of NLP in enhancing personality psychology and emphasizes the need for further interdisciplinary research to fully realize the capabilities of these transparent technologies.  \nIntroduction  \nLanguage is one of the most fascinating tools human beings have invented. Researchers in psychology have regarded it as a source of insights into the inner world, leading to groundbreaking discoveries about the interplay between language use and psychological characteristics. From Freud’s controversial analysis of slips ofthe tongue [1], through the use of selfreference pronouns to detect psychological phenomena [2–4] until more recent computational approaches, the field has evolved significantly [5] .  \nThe interest derived from language as a window to psychological features led into the words-as-attention premise that posits verbal behavior as a reflection of what someone is paying attention [6,7], and push the research into studying personality [8], life experiences [9], and even cultures [ 10], and societies [ 11] .  \nFunding: This research was supported by the Government of Catalonia  \n([https://govern.cat/gov/](https://govern.cat/gov/)), Grant number 2021SGR0709 receive","cbCaia8aMj6CYA6z","https://ap.wps.com/l/cbCaia8aMj6CYA6z","pdf",7616683,32,"English","# Abstract\n# Introduction\n# Funding\n# Competing interests","[{\"question\":\"What explainable AI method is central to the study?\",\"answer\":\"The article uses explainable AI techniques, particularly Integrated Gradients, to scrutinize how NLP models make decisions in personality assessment.\"},{\"question\":\"Which personality frameworks are compared?\",\"answer\":\"It compares typological models (MBTI) and dimensional models (Big Five) for classifying personality traits from text.\"},{\"question\":\"How are the NLP models trained and evaluated?\",\"answer\":\"The methodology applies log-odds ratio with an Informative Dirichlet Prior and uses fine-tuned transformer models including BERT and RoBERTa on the Essays and MBTI datasets.\"}]","Text speaks louder - Insights into personality from natural language processing | PDF",81]