[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-85667-en":3,"doc-seo-85667-105":29,"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":20,"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},85667,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Elite Proxies, Algorithmic Bottlenecks, and Multi-Platform Information Cascades in the 2026 Iran War","High-stakes executive crisis narratives increasingly emerge from closed broadcast enclaves and then spread across distinct open networks, yet cross-platform diffusion mechanisms remain under-theorized. This study tracks the transformation of President Trump’s 2026 Iran War statements as they move from Truth Social to X and Bluesky. Using a Metric-to-Semantic-Linkage framework and a dataset of 9,891 time-synchronized public responses, the research shows sociotechnical affordances drive behavioral divergence in downstream semantic framing.","Elite Proxies, Algorithmic Bottlenecks, and Multi-Platform Information  \nCascades in the 2026 Iran War  \nHakan Mehmetcik  \nVisiting Researcher, Kellogg Institute for International Studies, University of Notre Dame, IN, USA; Prof of International Relations, at the Faculty of Political Science, Marmara University,  \nIstanbul, Türkiye  \n[hakan.mehmetcik@marmara.edu.tr](hakan.mehmetcik@marmara.edu.tr)  \nORCID: 0000-0002-1882-4003  \nAbstract  \nAs high-stakes executive crisis discourse shifts to fragmented digital ecosystems, unmediated narratives increasingly originate in closed-broadcast enclaves before spreading across structurally distinct open-networks. Yet the mechanics of cross-platform information diffusion remain undertheorized, necessitating rigorous computational investigation. This study traces the mutation of President Trump's statements during the 2026 Iran War as they migrate from Truth Social to XTwitter and Bluesky. Utilizing a novel Metric-to-Semantic-Linkage framework and a highthroughput dataset of 9,891 temporally synchronized public response records, we examine how divergent platform architectures condition the downstream vernacular of geopolitical conflict. Our findings reveal a profound behavioral divergence driven by sociotechnical affordances. On XTwitter, discourse is dominated by structural information bottlenecks: viral retweet storms from elite proxy nodes compress lexical diversity and monopolize interpretive framing—with a single cascade accounting for 55.8% of the sub-corpus. Conversely, the decentralized Bluesky AT Protocol facilitates distributed, multi-vocal commentary characterized by analytical detachment and proportional coverage across all crisis events. These patterns are not products of architectural determinism alone but emerge from the interaction between platform affordances and localized user demographics. By operationalizing the decoupling of macro-engagement metrics from downstream semantic framing, this study advances the case for multi-platform comparative designs in computational political communication.  \nKeywords: executive communication, platform affordances, algorithmic bottlenecks, information cascades, computational social science  \n1. Introduction  \nThis study examines how information spreads across platforms by analyzing President Trump’suse of social media during the 2026 Iran War. As high-stakes executive crisis discourse has moved away from traditional institutional gatekeepers and into fragmented, highly polarized social media environments ([E. S. et](E. S. et) al. 2024), his messages often originate in specialized, relatively closed broadcast spaces—most notably Truth Social, which aligns with his established platform preferences (LaFraniere and Goldstein 2025; Linskey and DeBarros 2026) . Once these messages reach broader publics, however, they quickly move into expansive, structurally diverse open communication networks, where unmediated crisis communication can reshape public opinion, disrupt global financial and energy markets, and activate or intensify partisan subcultures under conditions of geopolitical volatility. Despite these stakes, the literature remains largely siloed within single-platform studies (Rowe and Alani 2014; Jordan 2018) and therefore does not adequately explain how a single narrative changes as it travels across distinct digital architectures (Tufekci 2014; Matassi and Boczkowski 2023) . To address this gap, our study adopts a comparative multi-platform design focused on two contrasting environments: centralized, algorithmically curated networks such as X-Twitter and decentralized, protocol-based networks such as Bluesky. This approach moves beyond literal text matching to examine how platform design, together with localized network demographics, shapes information cascades and the downstream vernacular of geopolitical conflict.  \nTo empirically map this cross-platform migration, this study utilizes a unique, high-throughput dataset consisting ","cbCaihTBASloU64J","https://ap.wps.com/l/cbCaihTBASloU64J","pdf",627596,1,28,"English","en",105,"# Introduction\n## Research Questions\n## Main Findings","[{\"question\":\"What is the main objective of the study?\",\"answer\":\"To explain how information diffusion changes when an identical executive crisis narrative migrates across structurally different social media platforms during the 2026 Iran War.\"},{\"question\":\"How does the study operationalize cross-platform migration?\",\"answer\":\"It uses a high-throughput dataset of 9,891 temporally synchronized public response records and a loose Boolean proximity harvesting pipeline to capture semantic ripples beyond exact-phrase matching.\"},{\"question\":\"What differences does the study find between X and Bluesky in how discourse develops?\",\"answer\":\"On X, discourse concentrates around structural information bottlenecks driven by viral retweet storms from elite proxy nodes, compressing lexical diversity. On Bluesky, the decentralized AT Protocol supports distributed, multi-vocal commentary with broader analytical and geographic/institutional coverage.\"}]",1784205487,71,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":27},"elite-proxies-algorithmic-bottlenecks-and-multi-platform-information-cascades-in-the-2026-iran-war","",{"@graph":35,"@context":85},[36,53,68],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/elite-proxies-algorithmic-bottlenecks-and-multi-platform-information-cascades-in-the-2026-iran-war/85667/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-17","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main objective of the study?","Question",{"text":75,"@type":76},"To explain how information diffusion changes when an identical executive crisis narrative migrates across structurally different social media platforms during the 2026 Iran War.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the study operationalize cross-platform migration?",{"text":80,"@type":76},"It uses a high-throughput dataset of 9,891 temporally synchronized public response records and a loose Boolean proximity harvesting pipeline to capture semantic ripples beyond exact-phrase matching.",{"name":82,"@type":73,"acceptedAnswer":83},"What differences does the study find between X and Bluesky in how discourse develops?",{"text":84,"@type":76},"On X, discourse concentrates around structural information bottlenecks driven by viral retweet storms from elite proxy nodes, compressing lexical diversity. On Bluesky, the decentralized AT Protocol supports distributed, multi-vocal commentary with broader analytical and geographic/institutional coverage.","https://schema.org",{"og:url":51,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":51},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":45,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":45,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":45,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":45,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":45,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":45,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":45,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]