Launcher nodes for detecting efficient influencers in social networks

Q1 Social Sciences Online Social Networks and Media Pub Date : 2021-09-01 DOI:10.1016/j.osnem.2021.100157
Pedro Martins , Filipa Alarcão Martins
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引用次数: 1

Abstract

Influence propagation in social networks is a subject of growing interest. A relevant issue in those networks involves the identification of key influencers. These players have an important role on viral marketing strategies and message propagation, including political propaganda and fake news. In effect, an important way to fight malicious usage on social networks is to understand their properties, their structure and the way messages propagate.

This paper proposes a new index for analyzing message propagation in social networks, based on the network topological nature and the influential power of the message. The new index characterizes the strength of each node as a launcher of the message, dividing the nodes into launchers and non-launchers. This division is most evident when the viral power of the message is high. Together with other known metrics, launcher individuals can assist to select efficient influencers in a social network. For instance, instead of choosing a strong member according to its degree in the network (number of followers), we may previously select those belonging to the launchers group and then look for the lowest degree members contained therein. These members are probably cheaper (on financial incentives) but still guarantying almost the same influence effectiveness as the largest degree members.

We discuss this index using a number of real-world social networks available in known datasets repositories.

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用于检测社交网络中有效影响者的启动节点
社交网络中的影响力传播是一个越来越受关注的主题。这些网络中的一个相关问题是确定关键的影响者。这些玩家在病毒式营销策略和信息传播(包括政治宣传和假新闻)方面发挥着重要作用。实际上,打击社交网络恶意使用的一个重要方法是了解它们的属性、结构和信息传播的方式。本文提出了一种基于网络拓扑性质和消息影响力的社交网络信息传播分析指标。新的索引描述了每个节点作为消息发布者的强度,将节点分为发布者和非发布者。当信息的病毒式传播能力很强时,这种分化最为明显。与其他已知指标一起,启动个人可以帮助在社交网络中选择有效的影响者。例如,不是根据其在网络中的程度(追随者数量)来选择一个强成员,我们可以先选择那些属于发射器组的成员,然后寻找其中包含的最低程度的成员。这些成员可能更便宜(在经济激励方面),但仍能保证与最高学位成员几乎相同的影响力。我们使用已知数据集存储库中可用的许多现实世界的社交网络来讨论这个索引。
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来源期刊
Online Social Networks and Media
Online Social Networks and Media Social Sciences-Communication
CiteScore
10.60
自引率
0.00%
发文量
32
审稿时长
44 days
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