[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117281-en":3,"doc-seo-117281-105":29,"detail-sidebar-cat-0-en-105":90},{"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":13,"seo_description":14,"update_tm":27,"read_time":28},117281,8796095461564,"Liam","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Enhancing Information Architecture with Machine Learning for Digital Media Platforms - Honors Thesis Proposal","Modern advancements in machine learning are reshaping information architecture within user experience design for digital media platforms. This work addresses the challenge created by rapidly growing volumes of user-generated data, where designers must categorize semantic content without breaking a user-centric interface structure. It highlights the need to connect backend classification and recommendation modeling with frontend information architecture decisions. The research aims to demonstrate an AI-informed information architecture model that supports a user-facing topic selection recommendation system.","Georgia Southern University  \nDigital Commons@Georgia Southern  \nHonors College Theses  \n4-1-2024  \nEnhancing Information Architecture with Machine Learning for Digital Media Platforms  \nTaylor N. Mietzner  \nGeorgia Southern University  \nFollow this and additional works at: [https://digitalcommons.georgiasouthern.edu/honors-theses](https://digitalcommons.georgiasouthern.edu/honors-theses)  \n Part of the Communication Technology and New Media Commons, Computer and Systems Architecture Commons, Graphic Design Commons, Other Computer Engineering Commons, and the Social Media Commons  \nRecommended Citation  \nMietzner, Taylor N., \"Enhancing Information Architecture with Machine Learning for Digital Media Platforms\" (2024) . Honors College Theses. 929.  \n[https://digitalcommons.georgiasouthern.edu/honors-theses/929](https://digitalcommons.georgiasouthern.edu/honors-theses/929)  \nThis thesis (open access) is brought to you for free and open access by Digital Commons@Georgia Southern. It has been accepted for inclusion in Honors College Theses by an authorized administrator of Digital Commons@Georgia Southern. For more information, please [contact digitalcommons@georgiasouthern.edu](contact digitalcommons@georgiasouthern.edu).  \nEnhancing Information Architecture with Machine Learning for Digital Media  \nPlatforms  \nAn Honors Thesis Proposal submitted in partial fulfillment of the requirements for Honors  \nin Information Technology.  \nBy  \nTaylor Mietzner  \nUnder the mentorship of Dr. Christopher Kadlec  \nABSTRACT  \nModern advancements in machine learning are transforming the technological landscape, including information architecture within user experience design. With the unparalleled amount of user data generated on online media platforms and applications, an adjustment in the design process to incorporate machine learning for categorizing the influx of semantic data while maintaining a user-centric structure is essential. Machine learning tools, such asthe classification and recommendation system, need to be incorporated into the design for user experience and marketing success. There is a current gap between incorporating the backend modeling algorithms and the frontend information architecture system design together. The aim of this research is to discover how machine learning technology can enhance the information architecture for user experience across multimedia platforms. For practical demonstration, there will be a novel, proposed information architecture model with machine learning input to recommend a topic selection system presented on the user-facing design.  \nThesis Mentor: Dr. Christopher Kadlec  \nHonors Dean: Dr. Steven Engel  \nApril 2024  \nInformation Technology  \nHonors College  \nGeorgia Southern University  \nAcknowledgements  \nI would like to express my sincere gratitude to the Department of Information Technology and the Honors College at Georgia Southern University. I am grateful for their commitment to my college learning and their abundant resources offered during my time at Georgia Southern University. I would also like to thank my mentor, Dr. Christopher Kadlec, for his dedication and willingness to help with my area of study. I would also like to express gratitude towards my parents, my husband, and friends for their support throughout my college journey.  \nTable of Contents  \n1. Introduction ........................................................................................................................................... 3  \n2. Literature Review ............................................................................................................................... 5  \n3. Case Study ............................................................................................................................................ 8  \n3.1. Problem Statement ........................................................................................................................ 8  \n3.2. Research ........","cbCaiqThXGBoej71","https://ap.wps.com/l/cbCaiqThXGBoej71","pdf",1534400,1,39,"English","en",105,"# Introduction\n# Literature Review\n# Case Study\n## Problem Statement\n## Research\n## Methodology\n## Proposed Model\n# Evaluation\n## Principles of User Experience Design and Information Architecture\n## Instagram Comparative Analysis\n## Facebook Comparative Analysis\n## YouTube Comparative Analysis\n# Limitations and Future Work\n# Conclusion\n# References","[{\"question\":\"Why is information architecture important for digital media platforms?\",\"answer\":\"Information architecture transforms raw data into accessible knowledge and guides users to consume, generate, organize, access, and display content through understandable interfaces.\"},{\"question\":\"What gap does the thesis identify between machine learning and information architecture design?\",\"answer\":\"It identifies a gap between integrating backend modeling algorithms and aligning those outputs with 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