ABSTRACT This paper aims to describe a new simplistic model dedicated to gauge the online influence of Twitter users based on a mixture of structural and interactional features. The model is an additive mathematical formulation which involves two main parts. The first part serves to measure the influence of the Twitter user on just his neighbourhood covering his followers. However, the second part evaluates the potential influence of the Twitter user beyond the circle of his followers. Particularly, it measures the likelihood that the tweets of the Twitter user will spread further within the social graph through the retweeting process. The model is tested on a data set involving four kinds of real-world egocentric networks. The empirical results reveal that an active ordinary user is more prominent than a non-active celebrity one. A simple comparison is conducted between the proposed model and two existing simplistic approaches. The results show that our model generates the most realistic influence scores due to its dealing with both explicit (structural and interactional) and implicit features.

中文翻译：

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在定向多重社交网络中识别突出网络用户的简单模型：使用 Twitter 网络的案例研究

摘要本文旨在描述一种新的简单模型，该模型致力于基于结构和交互特征的混合来衡量 Twitter 用户的在线影响。该模型是一种加法数学公式，涉及两个主要部分。第一部分用于衡量 Twitter 用户对其仅覆盖其追随者的社区的影响。但是，第二部分评估了 Twitter 用户在其粉丝圈之外的潜在影响力。特别是，它衡量了 Twitter 用户的推文通过转发过程在社交图谱中进一步传播的可能性。该模型在涉及四种现实世界以自我为中心的网络的数据集上进行了测试。实证结果表明，活跃的普通用户比不活跃的名人更为突出。在所提出的模型和两种现有的简单方法之间进行了简单的比较。结果表明，我们的模型由于处理显式（结构和交互）和隐式特征而产生最真实的影响分数。