[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-594141-105":59,"doc-detail-594141-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","predicting-english-word-concreteness-through-its-multidimensional-perceptual-and-action-strength-norms-read-online-free","Predicting English Word Concreteness Through Its Multidimensional Perceptual and Action Strength Norms - read online free","","Many datasets provide participant ratings for word norms and concreteness ratios, yet concreteness for infrequent words and non-words remains scarce. This study presents a statistical model to estimate concreteness for infrequent and newly encountered lexicons using Lancaster sensory-motor word norms. After removing missing values, a stepwise multiple linear regression selects the optimal subset of norms. Ten-fold cross-validation yields a residual mean standard error of 0.723 and R-square of 0.515, and 11 variables (except Head-mouth) serve as useful predictors.",{"@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/predicting-english-word-concreteness-through-its-multidimensional-perceptual-and-action-strength-norms-read-online-free/594141/",{"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/predicting-english-word-concreteness-through-its-multidimensional-perceptual-and-action-strength-norms-read-online-free/594141.png","ImageObject",300,407,{"name":92,"@type":93},"Kurz","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-25","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What gap does the study address about concreteness data?","Question",{"text":112,"@type":113},"Concreteness information for infrequent words and non-words is rare compared with richer resources for common words.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which norms are used to predict word concreteness?",{"text":117,"@type":113},"The model uses Lancaster sensory-motor word norms to predict concreteness ratios for an English word dataset.",{"name":119,"@type":110,"acceptedAnswer":120},"How is the predictive model validated and how well does it perform?",{"text":121,"@type":113},"The model is validated with 10-fold cross-validation, achieving residual mean standard error of 0.723 and R-square of 0.515.","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},594141,1792953170,{"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":8,"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":144,"read_time":41},2336478945635,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","| | \u003Cbr>Australian Journal of Applied Linguistics\u003Cbr>ISSN 2209-0959\u003Cbr>[https://www.castledown.com/journals/ajal/](https://www.castledown.com/journals/ajal/) |  |\n| --- | --- | --- |\n| Australian Journal of Applied Linguistics, 6(3), 176–187 (2024) [https://doi.org/10.29140/ajal.v6n3.1003](https://doi.org/10.29140/ajal.v6n3.1003) |  |  |\n| Predicting English Word Concreteness Through Its Multidimensional Perceptual and Action Strength Norms |  | |\n| MOHSEN DOLATABADI\u003Cbr>Tabita Modarres University, Department of Linguistics, Tehran, Iran\u003Cbr>[domohsen@yahoo.com](domohsen@yahoo.com) |  |  |\n| Abstract\u003Cbr>Many datasets resulting from participant ratings for word norms and also concreteness ratios are available. However, the concreteness information of infrequent words and non-words is rare. This work aims to propose a model for estimating the concreteness of infrequent and new lexicons. Here, we used Lancaster sensory-motor word norms to predict the word concreteness ratios of an English word dataset. After removing the missing values, we employed a stepwise multiple linear regression (SW-MLR) procedure for choosing an optimum number of norms to develop a predictive multiple regression model. Finally, we validate our model using 10-fold cross-validation. The final model could predict concreteness by Residual Mean Standard Error equal to 0.723 and R-Square of 0.515. Also, our results showed that all 11 variables of this dataset except the Head-mouth parameter are useful predictors. In conclusion, as a growing demand to know the concreteness values of non-words and also infrequent words is evident, our statistical method can pave the way for controlled experiments when choosing non-words as a stimulus is critical.\u003Cbr>Keywords: concreteness, prediction, perception, multiple linear regression. |  |  |\n| Introduction\u003Cbr>Why do people categorize some words as concrete and others as abstract? How can we predict the concept of concreteness value based on their embodied properties? The way we think about the world is intimately connected to our sensory-motor and action-effector perceptions, as suggested by Barsalou |  |  |\n\nCopyright: © 2024 MohsenDolatabadi. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within this paper.  \n(1999) and many other studies. These findings emphasize that when we conceptualize the world, we rely on the mechanisms that allow us to experience it firsthand. This process involves functional dependence on action, emotion, and perception systems (Barsalou, 2008) . Our brains use representations rooted in experiential methods, employing neural simulations or reenactments to deploy these representations (Barsalou et al., 2003) .  \nEmbodied cognition is a well-supported concept (Barsalou, 1999; Connell, 2019; Connell & Lynott, 2014b; Smith & Gasser, 2005; Vigliocco, Meteyard, Andrews & Kousta, 2009; Wilson, 2002) . It highlights that people perceive and understand the world through a combination of sensory-motor and action-effector perceptions. This perspective extends to mental representations of lexicons, as demonstrated by studies like Yao et al. (2020) . Research has consistently shown that we comprehend language by relating it to our interaction with the world, exemplified by idiomatic metaphors that activate both sensory-motor and abstract concept networks in the brain (Hellmann et al., 2013) . The conceptual metaphors offer valuable insights into individual differences, cognitive processes, and social interactions (Fetterman, French, and Meier, 2022; Gibbs, 2017) .  \nOne practical application of embodied cognition is seen in video instruction, which combines visual and auditory information to enhance learning (Lange & Costly, 2020) . This appr","cbCaicwZZ2pKnZYS","https://ap.wps.com/l/cbCaicwZZ2pKnZYS","pdf",421172,12,"English","# Abstract\n# Introduction\n## Embodied cognition and concreteness\n## Predicting concreteness from perceptual/action strengths\n## Datasets, infrequent words, and non-words\n## Clinical relevance and motivation","[{\"question\":\"What gap does the study address about concreteness data?\",\"answer\":\"Concreteness information for infrequent words and non-words is rare compared with richer resources for common words.\"},{\"question\":\"Which norms are used to predict word concreteness?\",\"answer\":\"The model uses Lancaster sensory-motor word norms to predict concreteness ratios for an English word dataset.\"},{\"question\":\"How is the predictive model validated and how well does it perform?\",\"answer\":\"The model is validated with 10-fold cross-validation, achieving residual mean standard error of 0.723 and R-square of 0.515.\"}]","Predicting English Word Concreteness Through Its Multidimensional Perceptual and Action Strength Norms - read online free | PDF",1792078610]