Cognitive Systems Research ( IF 3.9 ) Pub Date : 2021-03-19 , DOI: 10.1016/j.cogsys.2020.08.013 Lucas Johannes José Fijen , Julio Joaquín López González , Jan Treur
The persistence of information communicated between humans is difficult to measure as it is affected by many features. This paper presents an approach to computationally model the cognitive processes of information sharing to describe persistence or extinction of communication in Twitter over time. The adaptive mental network model explains, for example, how an individual can experience information overflow on a topic, and how this affects the sharing of information. Parameter tuning by Simulated Annealing is used to identify characteristics of the network model that fit to empirical data from Twitter. The data collected is related to the independentism in Catalunya, Spain, which is considered a global issue with repercussion in Europe.
中文翻译:
自适应时空因果网络模型,用于分析随着时间推移而出现的通信消亡
人与人之间交流的信息的持久性很难衡量,因为它受到许多功能的影响。本文提出了一种计算模型,用于对信息共享的认知过程进行建模,以描述Twitter中通信随时间的持续或消亡。自适应心理网络模型解释了例如个人如何体验有关某个主题的信息溢出,以及这如何影响信息共享。通过模拟退火进行参数调整用于识别适合于Twitter经验数据的网络模型特征。所收集的数据与西班牙加泰罗尼亚的独立主义有关,这被认为是欧洲在全球范围内引起反响的问题。