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确定“影响者”推特

Identifying 'Influencers' on Twitter
课程网址: http://videolectures.net/wsdm2011_mason_iit/  
主讲教师: Winter Mason
开课单位: 史蒂文斯理工学院
开课时间: 2011-08-09
课程语种: 英语
中文简介:
对于规划者,营销人员和社交网络研究人员来说,信息的口碑传播是非常有趣的。在这项工作中,我们通过跟踪2009年两个月间隔内在Twitter粉丝图上发生的3900万个融资事件来调查1.6M Twitter用户的属性和相对影响。我们发现最大的级联往往是由用户生成的过去一直有影响力的人,以及被机械土耳其人的工作人员评为更有趣和/或引起更多积极情感的网址。但是,对哪个用户或URL将生成大级联的单个级别预测相对不可靠。因此,我们得出结论,只有通过瞄准大量潜在影响者才能可靠地利用口碑传播,从而获得平均效果。最后,我们考虑一系列假设的营销策略,并发现在广泛的合理假设下,使用“普通影响者”可以实现最具成本效益的表现。 - 发挥平均甚至低于平均影响力的个人。
课程简介: Word-of-mouth diffusion of information is of great interest to planners, marketers and social network researchers alike. In this work we investigate the attributes and relative influence of 1.6M Twitter users by tracking 39 million di ffusion events that took place on the Twitter follower graph over a two month interval in 2009. We find that the largest cascades tend to be generated by users who have been influential in the past and from URLs that were rated more interesting and/or elicited more positive feelings by workers on Mechanical Turk. However, individual-level predictions of which user or URL will generate large cascades are relatively unreliable. We conclude, therefore, that word-of-mouth di ffusion can only be harnessed reliably by targeting large numbers of potential influencers, thereby capturing average e ffects. Finally, we consider a family of hypothetical marketing strategies, and fi nd that under a wide range of plausible assumptions the most cost-e ffective performance can be realized using "ordinary influencers" - individuals who exert average or even less-than-average influence.
关 键 词: Twitter; 营销策略; Mechanical Turk
课程来源: 视频讲座网
最后编审: 2020-05-31:吴雨秋(课程编辑志愿者)
阅读次数: 35