[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-82256-en":3,"doc-seo-82256-105":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},82256,962075114101,"Seraphina","https://ap-avatar.wpscdn.com/avatar/e000253a75eb197efd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780044092746381165",8,"Research & Report","Network-distance decay of perceived online social support","Perceived social support buffers stress, yet its relationship across graph distances in online social networks is not well understood. This work shows that inferred perceived online social support in a large avatar communication platform decays with network distance. Over the observed range, the decay fits a power-decay model better than a single exponential. Two-wave survey data and behavioral logs are combined, with a random forest used to infer support scores and regress Wave 2 on Wave 1 across hop distances.","arXiv :2607 .092 10v 1 [ cs . SI] 10 Jul 2026  \nNetwork-distance decay of perceived online social  \nsupport  \nMasanori Takano 1 ,2 ,∗ , Kenji Yokotani3 ,  \nMasaki Chujyo4 and Fujio Toriumi4  \n1 Multidisciplinary Information Science Center, CyberAgent, Inc. , Tokyo, Japan  \n2 Center of Advanced Research for Human-AI Symbiosis Society,  \nKeio University, Tokyo, Japan  \n3 Graduate School of Technology, Industrial and Social Sciences,  \nTokushima University, Tokushima, Japan  \n4 Graduate School of Engineering, The University of Tokyo, Tokyo, Japan  \n∗ Correspondence: [takano](takano masanori@cyberagent.co.jp)[ ](takano masanori@cyberagent.co.jp)[masanori@cyberagent.co.jp](takano masanori@cyberagent.co.jp)  \nAbstract  \nPerceived social support can buffer stress, but how it is associated across online social networks at different graph distances remains unclear. Here we show that inferred perceived online social support in a large avatar communication application decays with network distance in a form better described, over the observed range, by a powerdecay model than by a single exponential. We linked two-wave survey data from Pigg Party with behavioral logs, trained a random forest to infer perceived support for active users, and regressed Wave 2 scores on Wave 1 scores for users at hop distance k, adjusting for baseline support and covariates. Adjusted associations persisted across hops, consistent with power-law-like decay over the observed range. Individual-based simulations indicated that heterogeneous source-specific exponential decay rates can generate heavy-tailed aggregate decay. These results suggest that network position heterogeneity should be considered when characterizing distance-dependent associations among psychosocial states in online communities.  \n1 Introduction  \nMany collective phenomena in social networks are studied by assigning states to nodes and asking how these states are associated, transmitted, or correlated across edges [1, 2, 3] . Epidemic processes, information diffusion, and cooperative behavior provide standard examples in which local interactions generate macroscopic patterns over network distance [4, 5, 6, 7] . A central question in such systems is the shape of distance decay: whether an association  \nis essentially local, with a single characteristic length scale, or whether it persists across broader network neighborhoods. While this question has been extensively examined for infections, information, and behavioral cascades, it remains less clear how psychological states measured at the individual level are organized over graph distance in large online social networks.  \nHere, we focus on perceived online social support as such a node-level psychological state. Perceived social support represents an individual’s perception that sufficient social resources are available to provide emotional comfort, practical assistance, and guidance during challenging circumstances. This can buffer the harmful effects on mental health among people facing difficulties [8, 9], a phenomenon often referred to as the stress-buffering effect [10] . Online communities are especially relevant for studying this state because they can provide opportunities for support for people who lack social resources in the physical world, while reducing interpersonal risk and enabling flexible self-disclosure [12, 13, 14] . Avatar communication is a particularly informative setting: users interact through virtual bodies, facial expressions, and gestures in shared virtual spaces, enabling nonverbal, real-time interaction with online co-presence [15, 13] .  \nDigital platforms also enable the connection between psychological measurement and network structure. In offline settings, it is difficult to observe, at scale, who interacted with whom and for how long. By contrast, online communities record visits, replies, co-presence, follow relationships, and other interaction events, from which large-scale user networks can be constructed","cbCaiiLbrQdBhVoh","https://ap.wps.com/l/cbCaiiLbrQdBhVoh","pdf",2770998,1,23,"English","en",105,"# Abstract\n# Introduction\n## Background: distance decay in networks\n## Perceived online social support and stress buffering\n## Digital platforms and measurement from network structure\n## Modeling contrasts and study aim\n## Mechanisms for distance-conditioned associations","[{\"question\":\"What is the main goal of the study?\",\"answer\":\"To determine how perceived online social support is associated across different graph distances in large online social networks.\"},{\"question\":\"How is perceived online social support operationalized in the paper?\",\"answer\":\"As a psychological state measured via survey scores and inferred for active users by combining survey data with behavioral logs from an avatar communication application.\"},{\"question\":\"Which decay model better describes the relationship across network distance?\",\"answer\":\"A power-decay model describes the observed distance-dependent decline better than a single exponential, and the pattern is consistent with power-law-like decay across the studied range.\"}]",1784179201,58,{"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},"network-distance-decay-of-perceived-online-social-support","",{"@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/network-distance-decay-of-perceived-online-social-support/82256/",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 goal of the study?","Question",{"text":75,"@type":76},"To determine how perceived online social support is associated across different graph distances in large online social networks.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is perceived online social support operationalized in the paper?",{"text":80,"@type":76},"As a psychological state measured via survey scores and inferred for active users by combining survey data with behavioral logs from an avatar communication application.",{"name":82,"@type":73,"acceptedAnswer":83},"Which decay model better describes the relationship across network distance?",{"text":84,"@type":76},"A power-decay model describes the observed distance-dependent decline better than a single exponential, and the pattern is consistent with power-law-like decay across the studied 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