基于可见性图网络的中国专利申请关注度分析

Analysis of China’s Patent Application Concern Based on Visibility Graph Network

专利是创新的重要体现,很多人在进行专利申请之前会在网上对专利申请的过程进行查询,了解专利申请的步骤,这些人的搜索事实也是了解创新企业或个人对创新是否重视的一个手段。文中从一个全新的时间序列分析的视角即网络的角度,分析了关键字为“专利申请”的百度搜索指数时间序列的动力学特征。利用可见性图算法的原理将百度搜索指数时间序列转化为复杂网络,并计算其参数,分析其网络的拓扑结构。首先,通过计算2019年各省复杂网络的参数发现各省的专利关注度具有一定差异;其次,研究表明大多数网络均为无标度网络,原始时间序列具有分形的特征;最后通过聚类,可根据复杂网络的参数把31个省分为3类。文中分析了2011-2018年全国的百度搜索指数数据,通过社团结构的划分,可以发现时间序列的周期和中心节点对搜索指数影响的范围。

Patent is an important embodiment of innovation.Many people will inquire about the process of patent application on the Internet and learn the application steps before patent application.In fact,the online searching is also a way to know whether innovative enterprises or individuals attach importance to innovation.This paper analyzes the dynamic characteristics of Baidu search index time series with the keywords of“patent application”from the perspective of a new time series analysis,namely from the perspective of network.The time series of Baidu search index is transformed into a complex network by using the principle of visibility graph algorithm,and its parameters are calculated to analyze the topological structure of the network.Firstly,by calculating the complex network,it can be found that the patent attention of each province has certain differences.Secondly,the study shows that most of the networks are scale-free networks and the original time series have fractal characteristics.Finally,by clustering,31 provinces can be divided into 3 categories according to the characteristics of complex networks.This paper analyzes the data of Baidu search index from 2011 to 2018.By dividing the community structure,the time series period and the central node’s influence on the search index can be found.