文献类型：期刊文献

英文题名：Social Network Information Diffusion Model with Diverse User Forwarding Thresholds

作者：Sun, Qingsong[1]; He, Qihui[1]; Hu, Haibo[2]

机构：[1] School of Future Technology, Anhui Finance and Trade Vocational College, Hefei, 230601, China; [2] School of Business, East China University of Science and Technology, Shanghai, 200237, China

年份：2025

卷号：6

期号：4

起止页码：321

外文期刊名：Journal of Social Computing

收录：EI(收录号：20260319910145)

语种：英文

外文关键词：Diffusion - Marketing

摘要：Intuitively, social network users with more fans or friends can have a higher information forwarding threshold, however, previous studies seldom consider the threshold heterogeneity. This paper proposes an information diffusion model in which forwarding threshold is related to user degree. The results indicate that small-world networks have certain advantages compared with scale-free networks, but the difference is not obvious. The probability of forwarding information is positively related to the final proportion of known nodes, but there is an inflection point in the influence of this probability on the proportion of hesitant nodes. The proportions of known and hesitant nodes increase with the average degree of the networks. Known nodes decrease slowly as network size increases, whereas hesitant nodes show the opposite trend. As the strength of users' preference for information decreases, the proportion of known nodes first increases and then decreases. The peak number of known nodes is gradually delayed as the mean degree increases, but the proportion of hesitant nodes always decreases. The model can enhance the precision of diffusion predictions, offering actionable insights for applications such as targeted rumor control and optimized marketing strategies. ? 2020 Tsinghua University Press.