论文标题
在讨论过热期间，在线社交网络中用户动态的低频模式增加了
Increase of Low-Frequency Modes of User Dynamics in Online Social Networks During Overheating of Discussions
论文作者
论文摘要
在线社交网络中的用户动态不仅对在线社区，而且对现实世界的活动都有重大影响。作为示例，我们可以提及由社会两极分化，回声室现象，虚假新闻等触发的爆炸性用户动态。爆炸性用户动态通常被称为在线燃烧。基于波浪方程的在线社交网络模型（称为振荡模型）是一个理论模型，旨在描述在线社交网络中的用户动态。该模型可用于了解爆炸性用户动态与社交网络结构之间的关系。但是，由于将振荡模型作为社交网络的纯粹理论模型引入，因此有必要确认该模型是否正确描述了真实现象。在本文中，我们首先展示了振荡模型的预测。当在线社交网络的结构变化以激活用户活动时，用户动态的低频振荡模式将是主导的。为了通过实际数据验证预测，我们显示了电子公告板网站上帖子的日志数据的光谱分析以及Google趋势中搜索单词搜索的频率数据。结果支持理论模型的预测。
User dynamics in online social networks have a significant impact on not only the online community but also real-world activities. As examples, we can mention explosive user dynamics triggered by social polarization, echo chamber phenomena, fake news, etc. Explosive user dynamics are frequently called online flaming. The wave equation-based model for online social networks (called the oscillation model) is a theoretical model proposed to describe user dynamics in online social networks. This model can be used to understand the relationship between explosive user dynamics and the structure of social networks. However, since the oscillation model was introduced as a purely theoretical model of social networks, it is necessary to confirm whether the model describes real phenomena correctly or not. In this paper, we first show a prediction from the oscillation model; the low-frequency oscillation mode of user dynamics will be dominant when the structure of online social networks changes so that user activity is activated. To verify the predictions with actual data, we show spectral analyses of both the log data of posts on an electronic bulletin board site and the frequency data of word search from Google Trends. The results support the predictions from the theoretical model.
