Estimating influence of social media users from sampled social networks
Estimating influence of social media users from sampled social networks
复制标题
DOI：
10.1109/asonam.2016.7752405
复制
发表时间：
2016-08
期刊：
影响因子：
--
通讯作者：
K. Kimura;Sho Tsugawa
中科院分区：
文献类型：
--
作者：
K. Kimura;Sho Tsugawa
已经提出了几个评估社交媒体用户影响力的指标。大多数这样的指标是从代表社交媒体用户之间关系的社交网络的拓扑结构中获得的。然而，由于缺少数据、虚假数据或从社交网络中进行糟糕的节点/链接采样，这种社交网络结构中通常包含一些错误。在本文中，我们研究了来自社交网络的节点抽样对估计社交媒体用户影响的指标有效性的影响。我们将从抽样的社交网络中获得的用户的估计影响力与他们的实际影响力进行比较。我们的实验结果表明，使用偏抽样方法，如样本边缘计数，是一种比随机抽样更有效的估计用户影响力的方法，并且使用随机抽样来获得社交网络的结构会显著影响估计用户影响力的指标的有效性，这可能会使指标无效。
Several indices for estimating the influence of social media users have been proposed. Most such indices are obtained from the topological structure of a social network that represents relations among social media users. However, several errors are typically contained in such social network structures because of missing data, false data, or poor node/link sampling from the social network. In this paper, we investigate the effects of node sampling from a social network on the effectiveness of indices for estimating the influence of social media users. We compare the estimated influence of users, as obtained from a sampled social network, with their actual influence. Our experimental results show that using biased sampling methods, such as sample edge count, is a more effective approach than random sampling for estimating user influence, and that the use of random sampling to obtain the structure of a social network significantly affects the effectiveness of indices for estimating user influence, which may make indices useless.