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The study contrasts topic modeling, keyword-assisted topic modeling (keyATM), and supervised machine learning, with manual coding grounded in the Policy Frames codebook. Using 12 Austrian newspapers’ EU coverage (2009–2019), the results indicate supervised machine learning outperforms others, keyATM underperforms for frame analysis, while topic models offer a middle ground. Implications for measurement validity are discussed.",{"@graph":69,"@context":123},[70,84,106],{"@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/capturing-a-news-frame-comparing-machine-learning-approaches-to-frame-analysis-with-different-degrees-of-supervision-290599/290599/",{"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/capturing-a-news-frame-comparing-machine-learning-approaches-to-frame-analysis-with-different-degrees-of-supervision-290599/290599.png","ImageObject",300,407,{"name":92,"@type":93},"Ezra","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-18","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",12,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What three machine-learning approaches are compared for frame analysis?","Question",{"text":113,"@type":114},"The study contrasts topic modeling, keyword-assisted topic modeling (keyATM), and supervised machine learning.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How is the manual gold standard created in the study?",{"text":118,"@type":114},"Manual coding is based on the Policy Frames codebook, providing an established base for comparison.",{"name":120,"@type":111,"acceptedAnswer":121},"What data and time span are used to test the approaches?",{"text":122,"@type":114},"The analysis uses a large dataset of 12 Austrian newspapers’ EU coverage over 11 years, from 2009 to 2019.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},290599,1789642159,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":130,"read_time":145,"preview_page_count":4},1099514068035,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","UvA-DARE (Digital Academic Repository)  \nCapturing a News Frame  \nComparing Machine-Learning Approaches to Frame Analysis with Different Degrees of Supervision  \nEisele, O. ; Heidenreich, T. ; Litvyak, O. ; Boomgaarden, H.G.  \nDOI  \n10.1080/19312458.2023.2230560  \nPublication date  \n2023  \nDocument Version  \nFinal published version  \nPublished in  \nCommunication Methods and Measures  \nLicense  \nCC BY  \nLink to publication  \nCitation for published version (APA):  \nEisele, O. , Heidenreich, T. , Litvyak, O. , & Boomgaarden, H. G. (2023) . Capturing a News Frame: Comparing Machine-Learning Approaches to Frame Analysis with Different Degrees of Supervision. Communication Methods and Measures, 17(3), 205-226.  \n[https://doi.org/10.1080/19312458.2023.2230560](https://doi.org/10.1080/19312458.2023.2230560)  \nGeneral rights  \nIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons) .  \nDisclaimer/Complaints regulations  \nIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: [https://uba.uva.nl/en/contact](https://uba.uva.nl/en/contact), or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.  \nUvA-DARE is a service provided by the library of the University of Amsterdam ( [http](https://dare. uva. nl)[s](https://dare. uva. nl)[://dare. uva. nl](https://dare. uva. nl))  \nDownload date:18 Oct 2024  \nCOMMUNICATION METHODS AND MEASURES 2023, VOL. 17, NO. 3, 205–226  \n[https://doi.org/10.1080/19312458.2023.2230560](https://doi.org/10.1080/19312458.2023.2230560)  \nCapturing a News Frame – Comparing Machine-Learning Approaches to Frame Analysis with Different Degrees of Supervision  \nOlga Eisele a,b, Tobias Heidenreich a,c, Olga Litvyak a, and Hajo G. Boomgaarden a  \naDepartment of Communication, University of Vienna, Vienna, Austria; bAmsterdam School of Communication Research (ASCoR), University of Amsterdam, Amsterdam, the Netherlands; cThe Social Science Centre Berlin (WZB), Berlin, Germany  \nABSTRACT  \nThe empirical identification of frames drawing on automated text analysis has been discussed intensely with regard to the validity of measurements. Adding to an evolving discussion on automated frame identification, we systematically contrast different machine-learning approaches with a manually coded gold standard to shed light on the implications of using one or the other: (1) topic modeling,(2) keyword-assisted topic modeling (keyATM), and (3) supervised machine learning as three popular and/or promising approaches. Manual coding is based on the Policy Frames codebook, providing an established base that allows future research to dovetail our contribution. Analysing a large dataset of 12 Austrian newspapers’ EU coverage over 11 years (2009–2019), we contribute to addressing the methodological challenges that have emerged for social scientists interested in employing automated tools for frame analysis. While results confirm the superiority of supervised machine-learning, the semi-supervised approach (keyATM) seems unfit for frame analysis, whereas the topic model covers the middle ground. Results are extensively discussed regarding their implications for the validity of approaches.  \nIntroduction  \nFraming is among the most prominent conceptual approaches in the social sciences to classify communication contents. However, the academic debate about conceptualizing or operationalizinga frame has always been fractured (Entman, 1993) and has produced a plethora of literature discussing ","cbCaikqTydE7g4YB","https://ap.wps.com/l/cbCaikqTydE7g4YB","pdf",933131,23,"English","# Abstract\n# Introduction\n## Framing and frame identification challenges\n# Methodological comparison\n## Topic modeling\n## Keyword-assisted topic modeling (keyATM)\n## Supervised machine learning\n# Data and empirical setting\n## Austrian newspapers’ EU coverage (2009–2019)\n# Results\n## Supervised machine-learning performance\n## keyATM limitations\n## Topic models as a middle ground\n# Discussion\n## Validity implications for frame-analysis approaches","[{\"question\":\"What three machine-learning approaches are compared for frame analysis?\",\"answer\":\"The study contrasts topic modeling, keyword-assisted topic modeling (keyATM), and supervised machine learning.\"},{\"question\":\"How is the manual gold standard created in the study?\",\"answer\":\"Manual coding is based on the Policy Frames codebook, providing an established base for comparison.\"},{\"question\":\"What data and time span are used to test the approaches?\",\"answer\":\"The analysis uses a large dataset of 12 Austrian newspapers’ EU coverage over 11 years, from 2009 to 2019.\"}]","Capturing a News Frame - Comparing Machine-Learning Approaches to Frame Analysis with Different Degrees of Supervision | PDF",58]