Burbach Laura, Halbach Patrick, Ziefle Martina, Calero Valdez André
Human Computer Interaction Center, RWTH Aachen University, Aachen, Germany.
Front Artif Intell. 2020 Jul 2;3:45. doi: 10.3389/frai.2020.00045. eCollection 2020.
Today the majority of people uses online social networks not only to stay in contact with friends, but also to find information about relevant topics, or to spread information. While a lot of research has been conducted into opinion formation, only little is known about which factors influence whether a user of online social networks disseminates information or not. To answer this question, we created an agent-based model and simulated message spreading in social networks using a latent-process model. In our model, we varied four different content types, six different network types, and we varied between a model that includes a personality model for its agents and one that did not. We found that the network type has only a weak influence on the distribution of content, whereas the message type has a clear influence on how many users receive a message. Using a personality model helped achieved more realistic outcomes.
如今，大多数人使用在线社交网络不仅是为了与朋友保持联系，还为了查找有关相关主题的信息或传播信息。虽然已经对观点形成进行了大量研究，但对于哪些因素影响在线社交网络用户是否传播信息却知之甚少。为了回答这个问题，我们创建了一个基于代理的模型，并使用潜过程模型模拟社交网络中的信息传播。在我们的模型中，我们改变了四种不同的内容类型、六种不同的网络类型，并且在一个为其代理包含个性模型的模型和一个不包含个性模型的模型之间进行了变化。我们发现网络类型对内容的传播只有微弱的影响，而消息类型对有多少用户接收消息有明显的影响。使用个性模型有助于实现更现实的结果。
