论文标题
在线媒体上，逻辑方程的logistic方程的次要扩展：社会增长现象多样性的参数描述
A minor extension of the logistic equation for growth of word counts on online media: Parametric description of diversity of growth phenomena in society
论文作者
论文摘要
To understand the growing phenomena of new vocabulary on nationwide online social media, we analyzed monthly word count time series extracted from approximately 1 billion Japanese blog articles from 2007 to 2019. In particular, we first introduced the extended logistic equation by adding one parameter to the original equation and showed that the model can consistently reproduce various patterns of actual growth curves, such as the logistic function, linear growth, and finite-time divergence.其次，通过分析模型参数，我们发现典型的生长模式不仅是逻辑函数，它通常出现在各种复杂系统中，而且是一个非平凡的增长曲线，该曲线始于指数函数，并且渐近地接近无稳态状态的功率功能。此外，我们观察到了生长的功能形式与峰值峰值之间的联系。最后，我们证明了所提出的模型和统计属性对Google趋势数据（英语，法语，西班牙语和日语）也有效，这是全国范围内搜索查询的时间序列。
To understand the growing phenomena of new vocabulary on nationwide online social media, we analyzed monthly word count time series extracted from approximately 1 billion Japanese blog articles from 2007 to 2019. In particular, we first introduced the extended logistic equation by adding one parameter to the original equation and showed that the model can consistently reproduce various patterns of actual growth curves, such as the logistic function, linear growth, and finite-time divergence. Second, by analyzing the model parameters, we found that the typical growth pattern is not only a logistic function, which often appears in various complex systems, but also a nontrivial growth curve that starts with an exponential function and asymptotically approaches a power function without a steady state. Furthermore, we observed a connection between the functional form of growth and the peak-out. Finally, we showed that the proposed model and statistical properties are also valid for Google Trends data (English, French, Spanish, and Japanese), which is a time series of the nationwide popularity of search queries.
