{"title":"网络社区活动的多样性","authors":"T. Hogg, G. Szabó","doi":"10.1145/1379092.1379138","DOIUrl":null,"url":null,"abstract":"Web sites where users create and rate content as well as form links display many long-tailed distributions. Using one such site, Essembly, we propose causal mechanisms to explain these behaviors. Unlike purely descriptive models, our mechanisms use only information available to each user. We find the long-tails arise from large diversity of user activity and qualities of the rated content. The models not only explain overall behavior but also allow estimating the qualities of users and content from their early history on the site.","PeriodicalId":285799,"journal":{"name":"Proceedings of the nineteenth ACM conference on Hypertext and hypermedia","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Diversity of online community activities\",\"authors\":\"T. Hogg, G. Szabó\",\"doi\":\"10.1145/1379092.1379138\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Web sites where users create and rate content as well as form links display many long-tailed distributions. Using one such site, Essembly, we propose causal mechanisms to explain these behaviors. Unlike purely descriptive models, our mechanisms use only information available to each user. We find the long-tails arise from large diversity of user activity and qualities of the rated content. The models not only explain overall behavior but also allow estimating the qualities of users and content from their early history on the site.\",\"PeriodicalId\":285799,\"journal\":{\"name\":\"Proceedings of the nineteenth ACM conference on Hypertext and hypermedia\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the nineteenth ACM conference on Hypertext and hypermedia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1379092.1379138\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the nineteenth ACM conference on Hypertext and hypermedia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1379092.1379138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Web sites where users create and rate content as well as form links display many long-tailed distributions. Using one such site, Essembly, we propose causal mechanisms to explain these behaviors. Unlike purely descriptive models, our mechanisms use only information available to each user. We find the long-tails arise from large diversity of user activity and qualities of the rated content. The models not only explain overall behavior but also allow estimating the qualities of users and content from their early history on the site.