关键词: 创新扩散理论, 凝聚子群分析, 虚拟社区, 用户影响力, LT模型

Abstract:

In the field of node ranking research, few studies consider the influence of group norms on the propagation efficiency under the clustering effect, which may cause the accuracy of user influence measurement to decrease. In view of this problem, from the perspective of information diffusion, drawing on innovation diffusion theory and Bass diffusion model, a user local influence measurement model CSA-LL（Cohesive Subgroup Analysis Based Local Leadership）for virtual community networks is proposed：Based on the mining and analysis of condensed subgroups, the internal information diffusion efficiency of subgroups is defined, combined with the user’s global influence, the model output value is calculated as the basis for node ranking. Recent Douban community data are crawled for network construction, methods such as the AISAS model are used to verify that the users output by this model have stronger marketing capabilities than the results of the PageRank algorithm and Hits algorithm. The LT model is used to further verify the effectiveness of the model and the information diffusion efficiency of the subgroup has a positive effect on users’ communication ability. Multiple virtual community network data sets and IC models are used to verify the robustness of the conclusions.

Key words: innovation diffusion theory, condensed subgroup analysis, virtual communities, user influence, LT model