Chun Lo, Emilie de Longueau, Ankan Saha, S. Chatterjee
{"title":"Edge formation in Social Networks to Nurture Content Creators","authors":"Chun Lo, Emilie de Longueau, Ankan Saha, S. Chatterjee","doi":"10.1145/3366423.3380267","DOIUrl":null,"url":null,"abstract":"Social networks act as major content marketplaces where creators and consumers come together to share and consume various kinds of content. Content ranking applications (e.g., newsfeed, moments, notifications) and edge recommendation products (e.g., connect to members, follow celebrities or groups or hashtags) on such platforms aim at improving the consumer experience. In this work, we focus on the creator experience and specifically on improving edge recommendations to better serve creators in such ecosystems. The audience and reach of creators – individuals, celebrities, publishers and companies – are critically shaped by these edge recommendation products. Hence, incorporating creator utility in such recommendations can have a material impact on their success, and in turn, on the marketplace. In this paper, we (i) propose a general framework to incorporate creator utility in edge recommendations, (ii) devise a specific method to estimate edge-level creator utilities for currently unformed edges, (iii) outline the challenges of measurement and propose a practical experiment design, and finally (iv) discuss the implementation of our proposal at scale on LinkedIn, a professional network with 645M+ members, and report our findings.","PeriodicalId":20754,"journal":{"name":"Proceedings of The Web Conference 2020","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of The Web Conference 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3366423.3380267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Social networks act as major content marketplaces where creators and consumers come together to share and consume various kinds of content. Content ranking applications (e.g., newsfeed, moments, notifications) and edge recommendation products (e.g., connect to members, follow celebrities or groups or hashtags) on such platforms aim at improving the consumer experience. In this work, we focus on the creator experience and specifically on improving edge recommendations to better serve creators in such ecosystems. The audience and reach of creators – individuals, celebrities, publishers and companies – are critically shaped by these edge recommendation products. Hence, incorporating creator utility in such recommendations can have a material impact on their success, and in turn, on the marketplace. In this paper, we (i) propose a general framework to incorporate creator utility in edge recommendations, (ii) devise a specific method to estimate edge-level creator utilities for currently unformed edges, (iii) outline the challenges of measurement and propose a practical experiment design, and finally (iv) discuss the implementation of our proposal at scale on LinkedIn, a professional network with 645M+ members, and report our findings.