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Identification of opinion leader on rumor spreading in online social network Twitter using edge weighting and centrality measure weighting

机译:使用边缘权重和中心度度量权重确定关于在线社交网络Twitter中传言的舆论领袖

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Rumor spreading has been an essential issue for society. One of the platforms for rumor spreading is Twitter. Finding the opinion leader of its issue is also important in order to know who are users whom have a high impact of bringing the issue. So we can give the suggestion to the law authority to give the right authorization afterward. Opinion leader can be found using centrality measure metric on social network analysis study. This study has node and edge as its property. For recent years, there are many conducted researches about centrality measure. Some of them are combining some centrality measures together. Aside from defining the centrality measure, defining the edge is also important. Twitter has a different kind of relationships that can be turned into an edge, but not all the relationships have the same impact for spreading the rumor. This study conduct two experiments, first experiment is edge weighting. This experiment is aimed to see the importance of each defined edge type for finding the opinion leader. The second experiment is centrality weighting. This experiment is aimed to see the weight that could give more accurate opinion leader based on other evaluation algorithms. The study found the edge that has the ability to spread to wider audience (quote, retweet, and reply) tend to have a bigger impact for finding opinion leader than mention relationship. The study also finds that a low in-degree weight, high betweenness weight, and low or no PageRank weight could give 100% agreement upon other evaluation algorithms for finding the opinion leader.
机译:谣言传播一直是社会的基本问题。 Twitter是谣言传播的平台之一。找到问题的意见领袖也很重要,以便了解谁是带来问题影响很大的用户。因此,我们可以建议法律机关事后给予正确的授权。可以在社交网络分析研究中使用集中度度量来找到意见领袖。本研究以节点和边缘为属性。近年来,关于集中度测量的研究很多。其中一些正在将一些集中性措施结合在一起。除了定义中心度度量之外,定义边缘也很重要。 Twitter具有可以转变为优势的不同类型的关系,但是并非所有关系都对传播谣言具有相同的影响。这项研究进行了两个实验,第一个实验是边缘加权。该实验旨在了解每种定义的边类型对于找到意见领袖的重要性。第二个实验是集中度加权。本实验旨在查看可以基于其他评估算法为更准确的意见领袖提供帮助的权重。研究发现,能够传播给更多受众(引用,转发和回复)的优势通常比提及关系对寻找意见领袖具有更大的影响。这项研究还发现,度内权重低,中介度权重高以及PageRank权重低或不存在权重可以使其他评估算法找到意见领袖的可能性达到100%。

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