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Catching Social Butterflies: Identifying Influential Users of an Event-Based Social Networking Service

机译:赶上社会的蝴蝶:识别基于事件的社交网络服务的有影响力的用户

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Online social media information is often used as a proxy for unavailable or partially observed data on networks of offline contacts. This, in turn, requires an understanding of how close the proxy online structure is to the "true" offline social network. Social media tools such as Meetup that collect information about both online networks and their offline counterparts are of particularly importance as they shed more light on the (dis)similarity of online and offline contacts and highlight its potential causes. In this paper we examine structural (dis)similarities of the Meetup online and offline data, with a particular focus on geographical differences. We introduce a new measure called the event score to assess connections made by the most socially active individuals, or social butterflies. We apply the new social activity metric to determine which sorts of events are attended most by social butterflies and to evaluate how this aspect of the network structure differs across US cities.
机译:在线社交媒体信息通常用作离线联系人网络上不可用或部分观察到的数据的代理。反过来,这需要了解代理在线结构与“真正的”离线社交网络的接近程度。社交媒体工具(例如,Meetup)可收集有关在线网络及其离线对等物的信息,这一点尤为重要,因为它们使人们更加了解在线和离线联系的(不相似)之处,并突出了其潜在原因。在本文中,我们研究了Meetup在线和离线数据的结构(差异)相似性,特别关注地理差异。我们引入了一种新的衡量方法,即事件得分,以评估社交活动最活跃的人或社交蝴蝶之间的联系。我们应用新的社交活动指标来确定社交蝴蝶最参加的活动类型,并评估网络结构在美国各城市之间的差异。

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