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Analysis and evaluation of random-based message propagation models on the social networks

机译:社交网络上基于随机的消息传播模型的分析和评估

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Social network services (SNS), based on the complex relationships among people in real-life and virtual world, have become a major internet service for people to communicate with each other. Different social networks have different characteristics and varying levels of influence. To understand the message propagation process, the driving power behind it and its social influence, this paper presents a detailed analysis of message propagation models over the social networks by analyzing the relationships among nodes. This paper presents five proposed models which aim to analyze message propagations on social networks. We analyze the message propagation models and show how messages spread through the social networks. Furthermore, we propose a social network analysis on Hadoop platform to verify the social network characteristics. We also present a measurement study of messages collected from 900 K users on Facebook, to verify our proposed models by means of big-data Hadoop platform. We believe that our research provides valuable insights for future social network service research. (C) 2019PublishedbyElsevierB.V.
机译:基于现实生活和虚拟世界中人与人之间复杂关系的社交网络服务(SNS)已经成为人们相互交流的主要互联网服务。不同的社交网络具有不同的特征和不同程度的影响。为了了解消息传播过程,其背后的驱动力及其社会影响力,本文通过分析节点之间的关系,对社交网络上的消息传播模型进行了详细分析。本文提出了五个提议的模型,旨在分析社交网络上的消息传播。我们分析消息传播模型,并显示消息如何通过社交网络传播。此外,我们提出了在Hadoop平台上的社交网络分析,以验证社交网络的特征。我们还针对从Facebook上的90万用户收集的消息进行了度量研究,以通过大数据Hadoop平台验证我们提出的模型。我们相信我们的研究为未来的社交网络服务研究提供了宝贵的见识。 (C)2019由ElsevierB.V。发布

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