Information diffusion in Online Social Networks is a new and crucial problem in social network analysis field and requires significant research attention. Efficient diffusion of information are of critical importance in diverse situations such as; pandemic prevention, advertising, marketing etc. Although several mathematical models have been developed till date, but previous works lacked systematic analysis and exploration of the influence of neighborhood for information diffusion. In this paper, we have proposed Common Neighborhood Strategy (CNS) algorithm for information diffusion that demonstrates the role of common neighborhood in information propagation throughout the network. The performance of CNS algorithm is evaluated on several real-world datasets in terms of diffusion speed and diffusion outspread and compared with several widely used information diffusion models. Empirical results show CNS algorithm enables better information diffusion both in terms of diffusion speed and diffusion outspread.
翻译:在网上社会网络中,信息传播是社会网络分析领域一个新的关键问题,需要大量的研究关注。在诸如大流行病预防、广告、营销等不同情况下,信息的有效传播至关重要。虽然迄今为止已经开发了若干数学模型,但以前的工作没有系统地分析和探索邻里对信息传播的影响。在本文中,我们提出了用于信息传播的共同邻里战略算法,以显示共同邻里在整个网络信息传播中的作用。CNS算法的性能在传播速度和扩散范围方面根据几个真实世界数据集进行评估,并与一些广泛使用的信息传播模式进行比较。经验性结果显示,CNS算法有利于信息传播速度和扩散范围两方面的更好信息传播。