[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-293035-105":59,"doc-detail-293035-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","psyattention-psychological-attention-model-for-personality-detection","PsyAttention - Psychological Attention Model for Personality Detection","","Personality detection often relies on large sets of psychological features from different models such as BigFive and MBTI, yet mixing features computed under different standards can cause feature interference and degrade performance. This paper introduces PsyAttention to adapt multiple psychological models, effectively encoding psychological features while reducing their count by 85%. Experiments on BigFive and MBTI report average accuracies of 65.66% and 86.30%, outperforming state-of-the-art approaches and confirming the method’s effectiveness in psychological feature encoding.",{"@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/psyattention-psychological-attention-model-for-personality-detection/293035/",{"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/psyattention-psychological-attention-model-for-personality-detection/293035.png","ImageObject",300,407,{"name":92,"@type":93},"Well Done","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-26","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does PsyAttention address in personality detection?","Question",{"text":112,"@type":113},"It addresses interference caused by combining psychological features computed under different standards, which introduces noise and reduces performance.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does PsyAttention improve psychological feature encoding?",{"text":117,"@type":113},"It adapts different psychological models using PsyAttention, encoding psychological features and reducing their number by 85%.",{"name":119,"@type":110,"acceptedAnswer":120},"What results does the paper report for BigFive and MBTI?",{"text":121,"@type":113},"PsyAttention achieves average accuracy of 65.66% on BigFive and 86.30% on MBTI, outperforming state-of-the-art methods.","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},293035,1789658894,{"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":29,"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},5909892210082,"https://ap-avatar.wpscdn.com/avatar/56001069da27c9f41e8?x-image-process=image/resize,m_fixed,w_180,h_180&k=1789614185077863061","PsyAttention: Psychological Attention Model for Personality Detection  \nBaohua Zhang, Yongyi Huang, Wenyao Cui, Huaping Zhang ∗ and Jianyun Shang  \nBeijing Institute of Technology, China  \n[kevinzhang@bit.edu.cn](kevinzhang@bit.edu.cn)  \nAbstract  \nWork on personality detection has tended to incorporate psychological features from different personality models, such as BigFive and MBTI. There are more than 900 psychological features, each of which is helpful for personality detection. However, when used in combination, the application of different calculation standards among these features may result in interference between features calculated using distinct systems, thereby introducing noise and reducing performance. This paper adapts different psychological models in the proposed PsyAttention for personality detection, which can effectively encode psychological features, reducing their number by 85% . In experiments on the BigFive and MBTI models, PysAttention achieved average accuracy of 65.66% and 86.30%, respectively, outperforming state-ofthe-art methods, indicating that it is effective at encoding psychological features.  \n1 Introduction  \nPersonality detection helps people to manage themselves and understand themselves, and has been involved in job screening, personal assistants, recommendation systems, specialized health care, counseling psychotherapy, and political forecasting (Mehta et al., 2020b) . Personality measures originated from psychology (Pervin and John, 1999; Matthews et al., 2003), and psychologists judge their patients’ personality features through a series of tests.  \nThe content that users post on social media can give valuable insights into their personalities (Christian et al., 2021) . Personality detection can identify personality features from this, and often requires a combination of psychology, linguistics, and computer science.  \nThere are many psychological models of individual personality, the most famous being the BigFive (McCrae and Costa Jr, 1989; McCrae and  \nCorresponding author  \nJohn, 1992; Schmitt et al., 2008) and MBTI (Boyle, 1995; Hong, 2022; Celli and Lepri, 2018) . The BigFive model divides personality features into five factors(Digman, 1990): Openness (OPN), Conscientiousness (CON), Extraversion (EXT), Agreeableness (AGR), and Neuroticism (NEU) . These are usually assessed through questionnaires in which people reflect on their typical patterns of thinking and behavior. The MBTI model describes personality by 16 types that result from the combination of binary categories in four dimensions 1 : (1) Extraversion (E) vs Introversion (I); (2) Thinking (T) vs Feeling (F); (3) Sensing (S) vs Intuition (N); and (4) Judging (J) vs Perceiving (P) .  \nPrevious work saw a person’s use of language asa distillation of underlying drives, emotions, and thought patterns (Tausczik and Pennebaker, 2010;  \nBoyd and Pennebaker, 2017) . There are many theories and tools for extracting psychological features from texts, such as ARTE (Automatic Readability Tool For English) (Crossley et al., 2019), which has 55 psychological features); SEANCE (Sentiment Analysis And Cognition Engine) (Crossley et al., 2017), with 271 features; TAACO (Tool For The Automatic Analysis Of Cohesion) (Crossley et al., 2016), with 168 features; and TAALES (Tool For The Automatic Analysis Of Lexical Sophistication (Kyle and Crossley, 2015), with 491 features. These tools use multiple theories to obtain psychological features from text. For example, SEANCE uses eight theories, TAACO use fifteen theories. However, the application of different calculation standards among these features may result in interference between features calculated using distinct systems, thereby introducing noise and reducing performance. For example, when analyzing sentiment or emotion features, SEANCE uses more than 10 lexicons. A word’s meaning may vary according to the lexicon, which leads to inconsistencies  \n1[https://www.simplypsychology.org/the-m","cbCaidXXTFSnMWqI","https://ap.wps.com/l/cbCaidXXTFSnMWqI","pdf",1144581,14,"English","# Introduction\n## Related work","[{\"question\":\"What problem does PsyAttention address in personality detection?\",\"answer\":\"It addresses interference caused by combining psychological features computed under different standards, which introduces noise and reduces performance.\"},{\"question\":\"How does PsyAttention improve psychological feature encoding?\",\"answer\":\"It adapts different psychological models using PsyAttention, encoding psychological features and reducing their number by 85%.\"},{\"question\":\"What results does the paper report for BigFive and MBTI?\",\"answer\":\"PsyAttention achieves average accuracy of 65.66% on BigFive and 86.30% on MBTI, outperforming state-of-the-art methods.\"}]","PsyAttention - Psychological Attention Model for Personality Detection | PDF",35]