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Modeling information diffusion in online social networks using a modified forest-fire model

机译：使用改进的森林 - 火模型建模信息扩散在线社交网络

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摘要

Information dissemination has changed rapidly in recent years with the emergence of social media which provides online platforms for people worldwide to share their thoughts, activities, emotions, and build social relationships. Hence, modeling information diffusion has become an important area of research in the field of network analysis. It involves the mathematical modeling of the movement of information and study the information spread pattern. In this paper, we attempt to model information propagation in online social networks using a nature-inspired approach based on a modified forest-fire model. A slight spark can start a wildfire in a forest, and the spread of this fire depends on vegetation, weather, and topography, which may act as fuel. On similar lines, we labeled users who haven't joined the network yet asEmpty, existing users asTree, and information asFire. The spread of information across online social networks depends upon users-followers relationships, the significance of the topic, and other such features. We introduce a novelBurntstate to the traditional forest-fire model to represent non-spreaders in the network. We validate our method on six real-world data-sets extracted from Twitter and conclude that the proposed model performs reasonably well in predicting information diffusion.
机译：近年来，信息传播随着社交媒体的出现而迅速发生变化，该社会媒体为全球人民提供在线平台，以分享他们的思想，活动，情感和建立社会关系。因此，建模信息扩散已成为网络分析领域的重要研究领域。它涉及信息的运动和研究信息扩展模式的数学建模。在本文中，我们尝试使用基于修改的森林 - 火模型的自然启发方法在线社交网络中的信息传播。轻微的火花可以在森林里开始野火，这场火灾的传播取决于植被，天气和地形，这可能充当燃料。在类似的线条上，我们标记了没有加入网络且现有用户的用户的用户和信息ASFIRE。在线社交网络的信息传播取决于用户 - 追随者的关系，主题的重要性以及其他特征。我们向传统的森林 - 火模型介绍了一种新颖的燃烧室，以代表网络中的非传播者。我们在从Twitter中提取的六个真实数据集上验证了我们的方法，并得出结论，所提出的模型在预测信息扩散方面具有合理性。

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