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Using attractiveness model for actors ranking in social media networks

机译:使用吸引力模型对社交媒体网络中的演员进行排名

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Abstract Background Influential actors detection in social media such as Twitter or Facebook can play a major role in gathering opinions on particular topics, improving the marketing efficiency, predicting the trends, etc. Proposed methods This work aims to extend our formally defined T measure to present a new measure aiming to recognize the actor’s influence by the strength of attracting new important actors into a networked community. Therefore, we propose a model of the actor’s influence based on the attractiveness of the actor in relation to the number of other attractors with whom he/she has established connections over time. Results and conclusions Using an empirically collected social network for the underlying graph, we have applied the above-mentioned measure of influence in order to determine optimal seeds in a simulation of influence maximization. We study our extended measure in the context of information diffusion because this measure is based on a model of actors who attract others to be active members in a community. This corresponds to the idea of the IC simulation model which is used to identify the most important spreaders in a set of actors.
机译:摘要背景在诸如Twitter或Facebook之类的社交媒体中,有影响力的参与者检测可以在收集有关特定主题的意见,提高营销效率,预测趋势等方面发挥重要作用。建议的方法这项工作旨在将我们正式定义的T度量扩展到目前一项旨在通过吸引新的重要演员进入网络社区的力量来认识演员的影响的新措施。因此,我们根据演员的吸引力与他/她与之建立联系的其他吸引者的数量相关,提出了一个演员影响力的模型。结果与结论使用经验收集的社交网络作为基础图,我们已应用上述影响力测度,以便在影响力最大化的仿真中确定最佳种子。我们在信息传播的背景下研究扩展措施,因为该措施基于吸引其他人成为社区积极成员的行为者模型。这与IC仿真模型的思想相对应,该模型用于识别一组参与者中最重要的扩展器。

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