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Detecting the Influencer on Social Networks Using Passion Point and Measures of Information Propagation †

机译:使用激情点和信息传播测量检测社交网络上的影响因素†

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摘要

Influencer marketing is a modern method that uses influential users to approach goal customers easily and quickly. An online social network is a useful platform to detect the most effective influencer for a brand. Thus, we have an issue: how can we extract user data to determine an influencer? In this paper, a model for representing a social network based on users, tags, and the relationships among them, called the SNet model, is presented. A graph-based approach for computing the impact of users and the speed of information propagation, and measuring the favorite brand of a user and sharing the similar brand characteristics, called a passion point, is proposed. Therefore, we consider two main influential measures, including the extent of the influence on other people by the relationships between users and the concern to user’s tags, and the tag propagation through social pulse on the social network. Based on these, the problem of determining the influencer of a specific brand on a social network is solved. The results of this method are used to run the influencer marketing strategy in practice and have obtained positive results.
机译:影响者营销是一种现代方法,利用有影响力的用户轻松快速地接近目标客户。在线社交网络是一种检测品牌最有效的影响者的有用平台。因此,我们有一个问题:我们如何提取用户数据以确定影响者?在本文中,提出了一种基于用户,标签和它们之间的关系表示社交网络的模型,称为SNET模型。提出了一种基于图形的方法,用于计算用户的影响以及信息传播的速度,并测量用户最喜欢的品牌并共享类似品牌特征,称为激情点。因此,我们考虑两种主要的影响措施,包括用户与用户标签之间的关系对其他人的影响程度,以及通过社交网络上的社交脉冲的标签传播。基于这些,解决了在社交网络上确定了特定品牌的影响者的问题。该方法的结果用于在实践中运行影响者营销策略,并获得了积极的结果。

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