文献类型：期刊文献

中文题名：基于Lotka-Volterra模型的淘汰机制下的信息相互作用

英文题名：Information Interaction under Elimination Mechanism Based on Lotka-Volterra Model

作者：许楠楠[1];胡海波[1]

机构：[1]华东理工大学商学院,上海徐汇区200237

年份：2022

卷号：51

期号：3

起止页码：464

中文期刊名：电子科技大学学报

外文期刊名：Journal of University of Electronic Science and Technology of China

收录：CSTPCD;;EI(收录号：20222212173792);Scopus;北大核心:【北大核心2020】；CSCD:【CSCD2021_2022】；

基金：国家自然科学基金(61973121,71971082)。

语种：中文

中文关键词：信息扩散;信息相互作用;Lotka-Volterra模型;社交网络;泛娱乐事件

外文关键词：information diffusion;information interaction;Lotka-Volterra model;social network;pan-entertainment event

摘要：在考虑事件关键节点的情况下,研究社交网络中泛娱乐事件不同信息之间的相互作用。类比生态学中的种群竞争模型,将事件中晋级和淘汰选手相关信息的扩散看作不同类信息相互作用的结果,如争夺用户加入相关扩散网络中以增大扩散规模。结合对事件信息扩散不同阶段的划分,以“创造101”话题为例,构建Lotka-Volterra模型进行研究。实际数据拟合结果表明,事件的不同阶段信息相互作用会发生变化,前期的结果源于用户积累,后期则更依赖于粉丝效应,各类信息始终处于共存状态。节目中淘汰机制对选手信息的扩散有一定影响,但在粉丝效应下其影响有所减弱。扩散数据结合模型,能够量化线下事件进展对线上信息扩散的动态影响及信息间的相互作用,且可应用到其他类型信息交互研究中。
Considering the key points of events,this paper studied the interactions between different information in pan-entertainment events in social networks.By analogy with the population competition model in ecology,the diffusion process of relevant information to be promoted and eliminated players in events was regarded as the result of interaction between different types of information,such as competing with each other for users to join the relevant diffusion network to increase the diffusion scale.The paper combines the division of different stages of event information diffusion,and takes the topic of‘Produce 101’as an example to construct Lotka-Volterra model for research.The fitting results for the actual data show that information interactions change at different stages of the event.In the early stage,the results come from the accumulation of users,while in the later stage,it is more dependent on the fan effect,and all types of information are always in a state of coexistence.The elimination mechanism of the show has a certain influence on the diffusion of information about different players,but its influence will be weakened by the fan effect.Diffusion data combination model can quantify the dynamic impact of offline events on online information diffusion and the interaction between information,and can be applied to research on other types of information interaction.