{"title":"User behaviors in an Online Social Network","authors":"Dan Guo, Fuhong Lin, Changjia Chen","doi":"10.1109/ICNIDC.2009.5360901","DOIUrl":null,"url":null,"abstract":"In this paper, we focus on an Online Social Network (OSN), namely “kaixin-net” (www.kaixin001.com) which is one of the biggest OSNs in China. Based on studying the most popular game ‘Buying-a-house’, we investigate user behaviors. First, we made a model for “Buying-a-house”, then using the dataset that we crawled and traced (we crawled about one hundred and fifty user's profiles and traced forty users for about twenty days), we draw the following findings: (1) People who just join the game have much interest in this OSN, actively interact with his friends. (2) The interest goes down according to the time lapse for most of users, but there are also a few players whose interests never go down and enjoy this game very much. These can be interpreted as the population of kaixin-net is growing at the beginning state, but it will decline after the peak comes. So the organizers should think about how to slow down the peak's coming.","PeriodicalId":127306,"journal":{"name":"2009 IEEE International Conference on Network Infrastructure and Digital Content","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Network Infrastructure and Digital Content","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNIDC.2009.5360901","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper, we focus on an Online Social Network (OSN), namely “kaixin-net” (www.kaixin001.com) which is one of the biggest OSNs in China. Based on studying the most popular game ‘Buying-a-house’, we investigate user behaviors. First, we made a model for “Buying-a-house”, then using the dataset that we crawled and traced (we crawled about one hundred and fifty user's profiles and traced forty users for about twenty days), we draw the following findings: (1) People who just join the game have much interest in this OSN, actively interact with his friends. (2) The interest goes down according to the time lapse for most of users, but there are also a few players whose interests never go down and enjoy this game very much. These can be interpreted as the population of kaixin-net is growing at the beginning state, but it will decline after the peak comes. So the organizers should think about how to slow down the peak's coming.