多粒度专利视角下社交机器人发展态势研究

Development Trend Analysis of Social Bot based on Multi-granularity Patent Perspective

摘要:

本文对社交机器人专利进行多维多粒度研究，揭示其发展概况与关键技术演化态势，为社交机器人所在公共管理、舆情监测等不同应用中的发展部署提供决策支撑。首先，运用专利计量法从时间、地域等方面进行粗粒度分析，解释社交机器人技术发展趋势，挖掘技术热点。其次，提出关键词抽取与分级合作关系网挖掘方法，获取关键技术共现网络与发明人分级合作关系网络。最后，利用Neo4j图数据库和Gephi软件，实现社交机器人关键技术的细粒度分析与可视化展示。对Innography收录的社交机器人专利数据进行分析，得到该技术活动水平、地域流动关系，以及关键技术领域与发明人全局、分级合作关系网络。结果表明该方法能够较好的发现社交机器人技术主题与合作发展态势。

关键词:社交机器人技术;专利计量;关键技术共现网络;分级合作关系网络

Abstract:

This paper conducts multi-dimensional and multi-granularity research on social bot patents, which reveals its development profile and key technology trend. It provides decision support for the development and deployment of social bot in different applications such as public management and public opinion monitoring; First, we use the patent measurement method to conduct a coarse-grained analysis in terms of time, region, etc., to explain the development trend and explore technology hotspots of social bots technology. Secondly, the method of keyword extraction and hierarchical partnership network mining is proposed to obtain the key technology co-occurrence network and inventor hierarchical cooperative network. Finally, using Neo4j graph database and Gephi complex network analysis software, the fine-grained analysis and visual display of key technologies of social bots are realized; We analyze the patent data of social bots collected by Innography. The level of technical activities, regional mobility, and the global and hierarchical cooperation network between key technology fields and inventors are obtained. The results show that this method can better discover social bots technology topics and cooperative development trends.

Key words:Social Bots; Patentometrics; Co-occurrence Network of Key Technologies; Hierarchical Partnership Network