[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-151823-en":3,"doc-seo-151823-105":30,"detail-sidebar-cat-0-en-105":92},{"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":27,"seo_description":14,"update_tm":28,"read_time":29},151823,962084931830,"Jacob","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","FAIR NOTIFICATION OPTIMIZATION - AN AUCTION APPROACH","Fair Notification Optimization presents a centralized approach to curate mobile app notifications without overwhelming users. Multiple notification types are treated as buyers and send opportunities as items in an auction market, with the platform able to subsidize bids. Fairness is obtained using fair-division methods, including an Eisenberg–Gale-style convex program and its dual. From the dual, an online allocation strategy is built via first-price auctions with pacing multipliers, and an alternative second-price approach is introduced for better compatibility with existing ad systems. Production A/B testing and simulations on Instagram notifications compare both formats and evaluate stability, with second-price achieving better results for selected notification types.","FAIR NOTIFICATION OPTIMIZATION: AN AUCTION APPROACH  \narXiv :2302 .04835v 1 [ cs .GT] 9 Feb 2023  \nChristian Kroer  \nMeta and Columbia University USA  \nDeeksha Sinha, Xuan Zhang, Shiwen Cheng, Ziyu Zhou  \nMeta  \nUSA  \nABSTRACT  \nNotifications are important for the user experience in mobile apps and can influence their engagement. However, too many notifications can be disruptive for users. A typical mobile app usually has several types of notification, managed by distinct teams with objectives that are possibly conflicting with each other, or even with the overall platform objective. Therefore, there is a need for careful curation of notifications sent to users of these different types. In this work, we study a novel centralized approach for notification optimization, where we view the opportunities to send user notifications as items and types of notifications as buyers in an auction market. Furthermore, the auction setup is unique, and the platform has the ability to subsidize the bids from the notification types.  \nUsing tools from fair division, we study the application of competitive equilibrium for addressing this problem. We show that an Eisenberg-Gale-style convex program allows us to find an allocation that is fair to all notification types in hindsight. Using the dual of the formulation, we present an online algorithm that allocates notifications via first-price auctions using a pacing-multiplier approach. Secondly, we introduce an approach based on second-price auctions and pacing, which has the benefit of working well with existing advertising systems built for second-price auctions.  \nThrough an A/B test in production, we show that the second price-based auction system improves over a decentralized notification optimization system, leading to its launch in production for some Instagram notifications. Further, through simulations on Instagram notification data and a subsequent production A/B test, we compare the outcomes of first-price and second-price auctions and show that the former has more stable pacing multipliers.  \nKeywords Notification, Auction, Fair allocation  \n1 Introduction  \nNotifications are an important part of many mobile application (app) experiences. They inform users about promotions, new emails and messages, relevant activity in their social network, reminders about events such as birthdays, updates to threads they follow, etc. By serving as a communication channel for important information, notifications can influenceuser engagement on apps. Further, push / email notifications provide a way to communicate to users when they are not actively using the app. Though on the flip side, notifications can be a source of distraction and too many notifications can make users feel spammed. This can lead to users becoming habituated to ignoring notifications or turning off notifications, cutting off the possibility of any future communication through this channel. Thus, there is a need for careful curation of the notifications sent to users, sending only those that provide the most value to them.  \nFor the purpose of this curation, we need to understand the goals behind sending notifications. Often there are several types of notifications even within a single mobile app. For example, in a social media app, there can be notifications informing users about engagement (e.g., likes and comments) on their posts, new posts made by their friends, events such as birthdays, etc. For context, there are more than 550 types of notification in the Instagram app (see Figure 1 for some examples) . These notification types are managed by individual product teams, each having different goals. Typically, each team is responsible for choosing an appropriate set of notifications of that type to send to users. But this operating model has multiple shortcomings.  \nKroer, Sinha, Zhang, et al.  \nFigure 1: Sample of push notifications  \nDifferent teams can have goals that are not aligned with each other or with the overall platform 1 objectives. Thus, optimization o","cbCaisubkODrlAVG","https://ap.wps.com/l/cbCaisubkODrlAVG","pdf",1091349,1,20,"English","en",105,"# Introduction\n## Problem background: user experience and notification overload\n## Decentralized team management shortcomings\n## Centralized auction-based optimization framing\n## Relationship to fair sharing of attention in other platforms","[{\"question\":\"Why is notification optimization needed in mobile apps?\",\"answer\":\"Notifications shape engagement but can also distract users. Too many notifications may cause users to ignore or disable them, making future communication ineffective.\"},{\"question\":\"What model does the paper use to optimize notifications?\",\"answer\":\"The approach treats sending opportunities as items and notification types as buyers in an auction market. The platform can subsidize bids to support the mechanism.\"},{\"question\":\"How is fairness enforced across notification types?\",\"answer\":\"Fairness is achieved using tools from fair division, including an Eisenberg–Gale-style convex program. Its dual yields online allocation algorithms via first-price or second-price auctions with pacing.\"}]","FAIR NOTIFICATION OPTIMIZATION - AN AUCTION APPROACH | PDF",1787851013,50,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"fair-notification-optimization-an-auction-approach","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"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":53},"https://docshare.wps.com/document/fair-notification-optimization-an-auction-approach/151823/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-09-04","2026-08-27",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Why is notification optimization needed in mobile apps?","Question",{"text":76,"@type":77},"Notifications shape engagement but can also distract users. Too many notifications may cause users to ignore or disable them, making future communication ineffective.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What model does the paper use to optimize notifications?",{"text":81,"@type":77},"The approach treats sending opportunities as items and notification types as buyers in an auction market. The platform can subsidize bids to support the mechanism.",{"name":83,"@type":74,"acceptedAnswer":84},"How is fairness enforced across notification types?",{"text":85,"@type":77},"Fairness is achieved using tools from fair division, including an Eisenberg–Gale-style convex program. 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