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dc.contributor.authorChen, Xizh_CN
dc.contributor.authorGeng, Ruibinzh_CN
dc.contributor.authorCai, Shunzh_CN
dc.contributor.author蔡舜zh_CN
dc.date.accessioned2015-07-22T03:08:13Z
dc.date.available2015-07-22T03:08:13Z
dc.date.issued2014zh_CN
dc.identifier.citationElectronic Commerce Research and Applications, 2014zh_CN
dc.identifier.issn1567-4223zh_CN
dc.identifier.otherIP53211014zh_CN
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/87698
dc.description.abstractWith the rapid development of online social media, social networking services have become an important research area in recent years. In particular, microblogging as a new social media platform draws much attention from both researchers and practitioners. Although most current studies focus on the effect of social networks on the diffusion of services or information, most are descriptions or explanations of what has already happened. This study focuses on future activity by employing probability models such as the Pareto/NBD and BG/NBD models to predict user lifetime vitality. Three experiments were implemented to test the two models. Our results showed that both the Pareto/NBD model and the BG/NBD model were effective in predicting SNS user usage behavior on microblogging websites. It was found that tweeting behavior is more suitable for such probability models than retweeting behavior and user segmentation can improve prediction accuracy by distinguishing between currently active and inactive users. ? 2014 Elsevier B.V.zh_CN
dc.language.isoen_USzh_CN
dc.publisherElsevier B.V.zh_CN
dc.source.urihttp://dx.doi.org/10.1016/j.elerap.2014.06.001zh_CN
dc.subjectForecastingzh_CN
dc.subjectSocial networking (online)zh_CN
dc.titlePredicting microblog users' lifetime activities - A user-based analysiszh_CN
dc.typeArticlezh_CN


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