[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-158329-105":53,"doc-detail-158329-en":126},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":119,"head_meta":121,"extra_data":123,"updated_unix":125},105,"en","do-the-communities-we-choose-shape-our-political-beliefs-a-study-of-the-politicization-of-topics-in-online-social-groups","Do the Communities We Choose Shape our Political Beliefs? - A Study of the Politicization of Topics in Online Social Groups","","Social media has become a central venue for expressing and receiving political viewpoints, yet it also raises concerns that seemingly non-political interests become intertwined with political bias, intensifying polarization. This paper uses natural language processing to measure political bias in Reddit subcommunities and quantify how strongly topic selection correlates with politically biased language. Using topic discovery via Latent Dirichlet Allocation and bias measurement against external politically biased corpora, results show strong associations, with a classifier reaching 85.2% accuracy.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":46,"@type":70,"position":76},"https://docshare.wps.com/template/paper-templates/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/do-the-communities-we-choose-shape-our-political-beliefs-a-study-of-the-politicization-of-topics-in-online-social-groups/158329/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/do-the-communities-we-choose-shape-our-political-beliefs-a-study-of-the-politicization-of-topics-in-online-social-groups/158329.png","ImageObject",442,249,{"name":88,"@type":89},"WPS_1786070896","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-09-17","2026-08-29",true,{"@type":98,"interactionType":99,"userInteractionCount":9},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"How does the study measure political bias in Reddit subcommunities?","Question",{"text":108,"@type":109},"It determines political bias by comparing subcommunity language to external corpora of politically biased vocabulary, using direct comparison as the measurement method.","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"How are Reddit subcommunity topics identified in the paper?",{"text":113,"@type":109},"Reddit subcommunity topics are identified using a Latent Dirichlet Allocation model applied to the comment data.",{"name":115,"@type":106,"acceptedAnswer":116},"What evidence supports the link between topic features and politicized language?",{"text":117,"@type":109},"The paper trains a classifier on topic features and reports high accuracy of 85.2%, indicating strong correlations between group topic and politically biased language.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},158329,1787999384,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":45,"category_name":46,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":9,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":135,"language":136,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":61,"update_tm":125,"read_time":76},549768072016,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Do the Communities We Choose Shape our Political Beliefs? A Study of the Politicization of Topics in Online Social Groups  \nBenjamin Kane 1 and Jiebo Luo2  \nAbstract—Social media has become a ubiquitous part of the lives of many people, and provides a channel for ordinary people to voice and to hear political opinions. However, many believe that the rise of social media has lead to an increasing polarization of political views, with political bias becoming intertwined with seemingly non-political interests and behavior. In this paper, we aim to use natural language processing techniques to analyze the political bias of online social groups and the degree to which this bias correlates with non-political topics. Whereas this phenomenon has been studied extensively on networks such as Twitter, the popular social media domain Reddit has been relatively unexplored despite the structure of the platform allowing users to easily create their own interestbased subcommunities, thus providing an important and unique data source relevant to the topic at hand. This paper analyzes comment data from approximately 3,300 message boards on Reddit, with the goal of providing novel empirical knowledge about how group topic informs political bias in Reddit subcommunities. Topics of Reddit subcommunities are determined using a Latent Dirichlet Allocation model, and political bias of subcommunities is measured through direct comparison with external corpora of politically biased vocabulary; results are discussed within. Furthermore, to test the politicization of topics, we train a classifier on topic features to obtain a high accuracy of 85.2%(compared to a random-guessing baseline of 64.8%), suggesting fairly strong correlations between group topic and politically biased language in communities.  \nI. INTRODUCTION  \nWith the rising prevalence of the media in modern culture, many have voiced concern about the formation of online“echo chambers”, where users are selectively exposed to information which aligns with their political opinions (Barber et al. 2015; Mutz and Martin 2001) . Indeed, the tendency of people to divide themselves along political beliefs on internet blogs, news channels, and social media sites such as Twitter has been extensively documented (Adamic and Glance 2005; Iyengar and Hahn 2009; Yardi and Boyd 2010) although it has also been observed that rather than being systematically adverse to confrontational opinions, the phenomenon of selective exposure is primarily driven by a desire for opinion-reinforcement (Garrett 2009a; Garrett 2009b) .  \nThis latter tendency is related to homophily, the tendency for individuals to associate with similar others. Homophily has been shown to be a defining factor in the separation of individuals online into different social groups, based on both political factors (Colleoni, Rozza, and Arvidsson 2014)  \n1B. Kane is with the Department of Computer Science, University of Rochester, Rochester, NY 14627, USA.  \n2J. Luo is with Faculty of Computer Science, University of Rochester, Rochester, NY 14627, USA. [http://www.cs.rochester.edu/](http://www.cs.rochester.edu/)[ ](http://www.cs.rochester.edu/)[u/jluo/](u/jluo/)  \nas well as non-political factors (McPherson, Smith-Lovin, and Cook 2001) . Furthermore, an experimental study based on a social news aggregation site indicated a significant“herding effect” in how positive/negative comment votes were received, in which an arbitrary positive initial vote would lead to inflated subsequent scores (Muchnik, Aral, and Taylor 2013) .  \nAnother similar phenomenon linked with social media is the tendency for online social groups and subcommunities to form slight variations in language structure and vocabulary. For instance, a study of social cliques on IRC channels found a relationship between strong social network ties of a group and the use of in-group vernacular language variants (Paolillo 2001) . Social bonds online are often communicated through“ambient affiliatio","cbCaiftvNrE4276o","https://ap.wps.com/l/cbCaiftvNrE4276o","pdf",1504438,7,"English","# Abstract\n# Introduction\n## Echo chambers and selective exposure\n## Homophily and social group formation\n## Language variation and community memes\n## Partisan phrasing in political discourse\n## Research focus and approach","[{\"question\":\"How does the study measure political bias in Reddit subcommunities?\",\"answer\":\"It determines political bias by comparing subcommunity language to external corpora of politically biased vocabulary, using direct comparison as the measurement method.\"},{\"question\":\"How are Reddit subcommunity topics identified in the paper?\",\"answer\":\"Reddit subcommunity topics are identified using a Latent Dirichlet Allocation model applied to the comment data.\"},{\"question\":\"What evidence supports the link between topic features and politicized language?\",\"answer\":\"The paper trains a classifier on topic features and reports high accuracy of 85.2%, indicating strong correlations between group topic and politically biased language.\"}]","Do the Communities We Choose Shape our Political Beliefs? - A Study of the Politicization of Topics in Online Social Groups | PDF"]