[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-293630-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-293630-en":131},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","exploring-personality-traits-a-big-five-profiling-of-fictional-movie-characters","Exploring Personality Traits: A Big Five Profiling of Fictional Movie Characters","","The article develops and evaluates a personality profiling system for fictional movie characters using the Big Five model. A corpus was curated from movie scripts, then multiple traditional machine learning models were assessed alongside an LSTM approach for predicting personality traits from character dialogue and actions. The study reports that traditional machine learning methods outperform the LSTM model in this task context, supporting the feasibility of Big Five–based profiling from script-derived text.",{"@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/exploring-personality-traits-a-big-five-profiling-of-fictional-movie-characters/293630/",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/exploring-personality-traits-a-big-five-profiling-of-fictional-movie-characters/293630.png","ImageObject",300,407,{"name":42,"@type":43},"Nguyễn Văn Học","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-23","2026-09-17",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",14,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What personality framework is used for profiling the fictional movie characters?","Question",{"text":63,"@type":64},"The study uses the Big Five model, also called the Five Factor Model (OCEAN: Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism).","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How is the dataset for the study created?",{"text":68,"@type":64},"The authors curated a corpus sourced from movie scripts, using dialogues and actions from the fictional characters in the scripts.",{"name":70,"@type":61,"acceptedAnswer":71},"Which modeling approach performs best in the reported results?",{"text":72,"@type":64},"Traditional machine learning models outperform the LSTM model in this context for personality profiling based on the curated corpus.","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},293630,1789666601,{"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":112,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":80,"read_time":118,"preview_page_count":4},1374402739827,"https://ap-avatar.wpscdn.com/avatar/14000c97e7351f1a627?x-image-process=image/resize,m_fixed,w_180,h_180&k=1787885694763230660","ISSN 2007-9737  \nExploring Personality Traits: A Big Five Profiling  \nof Fictional Movie Characters  \nDiana Jimnez1 , Omar Jurez-Gambino2,* , Hiram Calvo1 , Elsy G. Cruz-Murrieta1  \n1 Instituto Politcnico Nacional,  \nCentro de Investigacin en Computacin, Mexico City,  \nMexico  \n2 Instituto Politcnico Nacional,  \nEscuela Superior de Cmputo, Mexico City,  \nMexico  \n[dianaljl.99@gmail.com](dianaljl.99@gmail.com), [jjuarezg@ipn.mx](jjuarezg@ipn.mx), [hcalvo@cic.ipn.com](hcalvo@cic.ipn.com), [ecruzm1601@alumno.ipn.mx](ecruzm1601@alumno.ipn.mx)  \nAbstract. In this article, we explore the viability of establishing a personality profiling system rooted in the Big Five model for movie characters. We curated a corpus sourced from movie scripts and proceeded to evaluate several traditional machine learning models alongside an LSTM model. Our findings indicate that traditional machine learning outperforms the LSTM model in this context.  \nKeywords. Personality profiling, big five, natural language processing.  \n1 Introduction  \nIn recent years, extensive research has been conducted on personality profiling based on text. Understanding the personality traits of individuals through their posts on platforms like Facebook or essays can serve various purposes. It can aid in tasks such as detecting psychological disorders, personalizing advertisements, and even identifying suitable candidates for employment [15, 12, 11] .  \nLarge Language Models (LLMs) have emerged as the gold standard for natural language generation. With LLMs [1, 7], we have the ability to imbue text with specific personality traits, allowing us to create dialogue or actions for characters in a manner that reflects their unique personalities [22, 24] .  \nThe prospect of automatically modeling characters with distinct personality and  \ntemperament using LLMs is particularly intriguing. However, to achieve this goal, our first step is to develop an automated system capable of verifying whether the generated text aligns with the intended personality traits.  \nIn related works, researchers have commonly utilized both the Myers-Briggs Type Indicator (MBTI) model and the Big Five [10] models for personality profiling. Despite the achievement of better metrics such as F1-Score and accuracy with the MBTI model [6], criticisms regarding its validity and reliability abound [17, 18, 5] .  \nConsequently, we opted to employ the Big Five model for our study. The Big Five model, also known as the Five Factor Model, offers a comprehensive framework for understanding and categorizing personality traits based on five key dimensions: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism (OCEAN) .  \nThe Big Five model has been extensively researched and validated across diverse populations and cultural contexts, making it a robust and well-established tool for personality assessment.  \nIts empirical foundation and cross-cultural applicability make it particularly suitable for our purposes of character profiling and classification [20, 21] .  \nComputación y Sistemas, Vol. 28, No. 4, 2024, pp. 2243–2250 doi: 10. 13053/CyS-28-4-5294  \nISSN 2007-9737  \n2244 Diana Jiménez, Omar Juárez-Gambino, Hiram Calvo, et al.  \nFig. 1. The distribution of dialogues (including direct speech and actions) for each big five traits across the current corpus  \nFig. 2. The distribution of characters for each Big Five traits across the current corpus  \n2 Related Work  \nPredicting personality traits from social media has become increasingly popular due to the potential to leverage this information to enhance user interactions across a wide range of computerized platforms and interfaces. The authors of [14] carried out a comparison between classifiers in WEKA (Bayes, Functions, Rules, Trees, and Meta) for predicting student personality traits using Twitter data. Only extraversion from the Big Five model was considered. Four correlated profile features were selected and mapped. Evaluation using 10-fold c","cbCaiaDHb0XMqNUK","https://ap.wps.com/l/cbCaiaDHb0XMqNUK","pdf",661882,"English","# Introduction\n## Related Work","[{\"question\":\"What personality framework is used for profiling the fictional movie characters?\",\"answer\":\"The study uses the Big Five model, also called the Five Factor Model (OCEAN: Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism).\"},{\"question\":\"How is the dataset for the study created?\",\"answer\":\"The authors curated a corpus sourced from movie scripts, using dialogues and actions from the fictional characters in the scripts.\"},{\"question\":\"Which modeling approach performs best in the reported results?\",\"answer\":\"Traditional machine learning models outperform the LSTM model in this context for personality profiling based on the curated corpus.\"}]","Exploring Personality Traits: A Big Five Profiling of Fictional Movie Characters | PDF"]