Eduardo Hargreaves, D. Menasché, Giovanni Neglia, Claudio Agosti
{"title":"Visibilidade no Facebook: Modelos, Medições e Implicações","authors":"Eduardo Hargreaves, D. Menasché, Giovanni Neglia, Claudio Agosti","doi":"10.5753/BRASNAM.2018.3591","DOIUrl":null,"url":null,"abstract":"Facebook news feed personalization algorithm has a significant impact, on a daily basis, on the lifestyle, mood and opinion of millions of Internet users. Nonetheless, such algorithms lack transparency challenging researchers to improve their fairness and accountability. In this paper, we propose a model to capture the dynamics of contents over a timeline (also known as news feed). The input to our model is a fundamental quantity associated to timelines, which we show that can be easily parameterized using real world data: the arrival rate of posts of a given publisher followed by the user. Using real world Facebook traces from the latest elections in Italy, we validate the accuracy of the proposed model and use the model for conterfactual what-if analysis.","PeriodicalId":428504,"journal":{"name":"Anais do Brazilian Workshop on Social Network Analysis and Mining (BraSNAM)","volume":"142 9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anais do Brazilian Workshop on Social Network Analysis and Mining (BraSNAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5753/BRASNAM.2018.3591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Facebook news feed personalization algorithm has a significant impact, on a daily basis, on the lifestyle, mood and opinion of millions of Internet users. Nonetheless, such algorithms lack transparency challenging researchers to improve their fairness and accountability. In this paper, we propose a model to capture the dynamics of contents over a timeline (also known as news feed). The input to our model is a fundamental quantity associated to timelines, which we show that can be easily parameterized using real world data: the arrival rate of posts of a given publisher followed by the user. Using real world Facebook traces from the latest elections in Italy, we validate the accuracy of the proposed model and use the model for conterfactual what-if analysis.