[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121564-en":3,"doc-seo-121564-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121564,13056703020460,"Valentina","https://ap-avatar.wpscdn.com/avatar/be000253dac470eee5d?_k=1778207105932848923",8,"Research & Report","Leveraging Machine Learning for Automated Semantic Analysis in Novel Writing - Bridging Literature and Computational Linguistics","This paper explores how machine learning can support semantic analysis in novel writing by connecting literary creativity with computational linguistics. Using state-of-the-art unsupervised and supervised learning approaches, it examines narrative consistency, characterisation, and theme consistency. Instead of relying on conventional NLP pipelines, it proposes graph-based machine learning, transformer-based contextual representations, and vector representations to build semantic models. The framework provides real-time feedback by identifying stylistic patterns and anomalies, helping authors refine plots while preserving artistic freedom.","2025 International Conference on Recent Innovation in Science Engineering and Technology (ICRISET) | 979-8-33 15-5833-8/25/$31.00 ©2025 IEEE | DOI: 10. 1 109/ICRISET64803 .2025. 11251798  \nLeveraging Machine Learning for Automated Semantic Analysis in Novel Writing: Bridging Literature and Computational Linguistics  \nGarima Chauhan1, Naresh S2, Chhavi Kulshreshtha3, Asih Wiarsih4, Sashka Jovanovska5, Nidal Al Said6  \n1Vivekananda Global University, Jaipur, India  \n2Department of English S.A. College of Arts &Science,Chennai, Tamil Nadu,India  \n3Manav Rachna University Haryana,India  \n4Universitas Sindang Kasih Majalengka, Indonesia.  \n5Department of English Language and Literature Faculty of Philology-GoceDelcev University KrsteMisirkov bb, Stip, Republic of  \nNorth Macedonia.  \n6College of Mass Communication, Ajman University, Ajman, UAE.  \n[Emailid:Garima.chauhan@vgu.ac.in](Emailid:Garima.chauhan@vgu.ac.in), [thinkpubls@gmail.com](thinkpubls@gmail.com), [thinkpubls@gmail.com](thinkpubls@gmail.com), [asihwiarsih@uskm.ac.id](asihwiarsih@uskm.ac.id),  \n[saska.jovanovska@ugd.edu.mk](saska.jovanovska@ugd.edu.mk),[n.alsaid@ajman.ac.ae](n.alsaid@ajman.ac.ae)  \nAbstract-The paper will attempt to find a solution to how machine learning can be used in the semantic analysis of novel writing, as this is a way to merge the difference between literary creativeness and computational linguistics. Based on the use of the state of art unsupervised and supervised learning algorithms we examine narrative consistency, characterisation, and theme consistency as aspects that can be analysed in literary works. Rather than depending on conventional natural language processing pipelines, the proposed research focuses on graph-based machine learning and transformer-based context representation as well as vector representation to derive semantic models. The aim is to assist authors in learning how to perfect a plot and enrich its semantics, not losing artistic freedom. The given framework provides real-time feedback, identification of stylistic patterns and anomalies in plot development which is a significant contribution in literature-sensitive machine intelligence.  \nKeywords: Semantic Analysis, Machine Learning, Narrative Coherence, Computational Literature, Character Development, Transformer Models.  \nI.INTRODUCTION  \nComputational techniques and literature production can no longer be an imaginative domain but are becoming a real-life condition as machine learning is changing and revolutionizing several areas of literary crafting. Specifically, semantic analysis, which has had its historical dependence on human interpretation and interpretation, has also become an area where the algorithm might play a significant role in comprehension and improving content in written works. Semantic analysis in the context of  \nnovel writing will entail unravelling of deep narrative structures, deep narrative structures, detection of recurring motifs, adoption of a character consistency, and involve following the theme development [1] .  \nThe latest improvements in the field of machine learning enable the development of intelligent systems which are able to do more than count the frequency of words or check syntax on the surface level. In this paper we explore how graph neural networks, deep contextual embeddings (i.e., transformer-based models like BERT and RoBERTa) and semantic vectorization (e.g. what sentence transformers can offer) can be used to automate the process of semantic evaluation of longform literary texts. These devices enable us to comprehend not only the content of a statement but the way, the time and the person saying it in order to promote more logical plot development and multidimensional narrations.  \nThe proposed system in this article does not depend on the well-established Natural Language Processing (NLP) pipelines, however, implements the representations learning properties of machine learning. These approaches define the textual semanti","cbCaicRKrCOCi57z","https://ap.wps.com/l/cbCaicRKrCOCi57z","pdf",3432025,1,6,"English","en",105,"# Introduction\n# Related Works","[{\"question\":\"How does the paper propose using machine learning for semantic analysis in novel writing?\",\"answer\":\"It proposes graph-based machine learning and transformer-based context representation with vector representations to derive semantic models for narrative evaluation.\"},{\"question\":\"Which narrative aspects does the approach target?\",\"answer\":\"It targets narrative consistency, characterisation, and theme consistency, including coherence across plot development.\"},{\"question\":\"What kind of support does the framework provide to authors?\",\"answer\":\"It offers real-time feedback, identifying stylistic patterns and anomalies in plot development to help authors improve pacing and reduce issues like character drift or theme imbalance.\"}]","Leveraging Machine Learning for Automated Semantic Analysis in Novel Writing - Bridging Literature and Computational Linguistics | PDF",1785736263,15,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"leveraging-machine-learning-for-automated-semantic-analysis-in-novel-writing-bridging-literature-and-computational-linguistics","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/leveraging-machine-learning-for-automated-semantic-analysis-in-novel-writing-bridging-literature-and-computational-linguistics/121564/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"How does the paper propose using machine learning for semantic analysis in novel writing?","Question",{"text":75,"@type":76},"It proposes graph-based machine learning and transformer-based context representation with vector representations to derive semantic models for narrative evaluation.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which narrative aspects does the approach target?",{"text":80,"@type":76},"It targets narrative consistency, characterisation, and theme consistency, including coherence across plot development.",{"name":82,"@type":73,"acceptedAnswer":83},"What kind of support does the framework provide to authors?",{"text":84,"@type":76},"It offers real-time feedback, identifying stylistic patterns and anomalies in plot development to help authors improve pacing and reduce issues like character drift or theme imbalance.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,114,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]