[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84381-en":3,"doc-seo-84381-105":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":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},84381,13056703020460,"Valentina","https://ap-avatar.wpscdn.com/avatar/be000253dac470eee5d?_k=1778207105932848923",8,"Research & Report","Rumour Spreading In Community Based Networks","Community-structured networks feature dense links inside groups and sparser connections between groups, which strongly shape outcomes of spreading processes such as disease transmission or information flow. The work studies rumour spreading on networks parameterised by within-group connectivity and between-group connectivity, showing that community topology differs from commonly used small-world or random network assumptions. Results indicate that network structure exerts a measurable effect on rumour propagation dynamics even when the influence is limited.","Rumour Spreading In Community Based Networks  \nZhaoxi Cui and Anthony O‘Hare  \nComputing Science and Mathematics, University of Stirling  \nStirling, FK9 4LA. United Kingdom  \n(Dated: July 10, 2026)  \nMany real-world networks have the characteristic that they are comprised of distinct groups or communities whose members contain many links within the community but with fewer connections to others. It is important to accurately model these types of networks to correctly predict the outcome of important spreading processes such as disease transmission, or the flow of information etc. Our motivating example is a network of traders within several investment institutions such ashedge funds. We assume an idealised scenario where traders within the same institution have many contacts and can share information quickly and easily but have fewer contacts to traders in other institutions, relying on personal networks, allowing for information to flow easily within a community and less-so between communities. In this paper we investigate a particular spreading process, the spread of a rumour, on a community based network that is characterised by two parameters; the within-group connectivity, and the between-group connectivity. We show that such networks have different characteristics to small-world or random networks that are often used to model the types of systems and that the network topology has a small but not insignificant effect on the spread of rumours on the network.  \narXiv :2607 .08546v 1 [ cs . SI] 9 Jul 2026  \nI. INTRODUCTION  \nOne of the earliest models to describe the spread of rumours used a probabilistic approach to describe the transitioning of individuals between different states based on their exposure to a rumour [1, 2] in a similar way epidemic models are used to study the spread of disease ina population [3] . Daley and Kendall [2] formulated a model to simulate the spread of rumour, by conceptualising a closed, homogeneously mixing population and dividing it into three mutually exclusive and exhaustive categories; Ignorants (I), individuals who have not heard the rumour, Spreaders (S), individuals who have heard the rumour and are actively spreading it, and Stiflers (R), individuals who have heard the rumour but have stopped spreading it, either due to disbelief, lack of interest, or because the rumour has reached a saturation point where it is no longer deemed ‘news’. The DK model was formulated as a system of differential equations to describe the transitions between these states, drawing parallels to the SIR (Susceptible-Infected-Removed) model in epidemiology [3] .  \nWhile the Daley-Kendall (DK) model provides a foundational understanding of rumour dynamics, subsequent research has introduced several variations and extensions to better capture the complexities of real-world information spread. These modified models incorporate additional parameters and mechanisms, allowing for more nuanced representations of how rumours propagate through diverse social networks.  \nThe Maki-Thompson model [4] simplifies the DaleyKendall model by focussing on direct contacts rather than pairwise interactions and only the initiating spreader becomes a stifler when meeting another spreader. The Maki-Thompson model was one of the first to incorporate stochastic elements to account for the inherent randomness in rumour spreading; using a  \nMarkov chain framework to describe the transitions between states, providing a more realistic representation of rumour dynamics.  \nDespite similarities with epidemiological models, the distinct recovery rule causes fundamental differences in the rumour-free equilibrium. In contrast to the selfdecay process in the disease spreading model, the stifling mechanism in the rumour spreading process highlightsa contact-based transition; the spreaders become stifled only as a result of encountering those who are already aware of the rumour whereas in an epidemiology model, infected individuals recover such th","cbCaicUzPOrcUTmh","https://ap.wps.com/l/cbCaicUzPOrcUTmh","pdf",1796054,4,1,11,"English","en",105,"# Introduction\n## Classical rumour models (DK, MK)\n## Rumour propagation on networks\n## Network-structure extensions and thresholds","[{\"question\":\"What are the three states in the Daley–Kendall (DK) rumour model?\",\"answer\":\"Individuals are classified as Ignorants (I), Spreaders (S), and Stiflers (R). Spreaders stop spreading after encountering the rumour-aware individuals, differing from epidemiological recovery rules.\"},{\"question\":\"How does the Maki–Thompson (MK) model differ from DK?\",\"answer\":\"MK simplifies DK by focusing on direct contacts rather than pairwise interactions and makes only the initiating spreader transition to a stifler when it meets another spreader, using a stochastic framework.\"},{\"question\":\"Which factors determine rumour spreading in the community-based network studied in the paper?\",\"answer\":\"The model characterises the network by two parameters: within-group connectivity and between-group connectivity. These parameters shape how efficiently rumours spread inside communities compared with across communities.\"}]",1784195208,28,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"rumour-spreading-in-community-based-networks","",{"@graph":36,"@context":85},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":21},"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":20},"https://docshare.wps.com/document/rumour-spreading-in-community-based-networks/84381/",{"url":52,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-27","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 are the three states in the Daley–Kendall (DK) rumour model?","Question",{"text":75,"@type":76},"Individuals are classified as Ignorants (I), Spreaders (S), and Stiflers (R). Spreaders stop spreading after encountering the rumour-aware individuals, differing from epidemiological recovery rules.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the Maki–Thompson (MK) model differ from DK?",{"text":80,"@type":76},"MK simplifies DK by focusing on direct contacts rather than pairwise interactions and makes only the initiating spreader transition to a stifler when it meets another spreader, using a stochastic framework.",{"name":82,"@type":73,"acceptedAnswer":83},"Which factors determine rumour spreading in the community-based network studied in the paper?",{"text":84,"@type":76},"The model characterises the network by two parameters: within-group connectivity and between-group connectivity. These parameters shape how efficiently rumours spread inside communities compared with across communities.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":21,"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":20,"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":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]