Construction of sentimental knowledge graph of Chinese government policy comments

ABSTRACT

Social Media Networks have developed into an important channel and platform for the collection and dissemination of policy information. Various policy comments on them have fully demonstrated the basic characteristics of big data. This paper introduces knowledge graphs into the sentiment analysis, analyses and sorts out the policy comments of China's mainstream social media platforms from 2016 to 2019, build a sentiment analysis dictionary, and then use the policy comments evaluation system to form sentiment knowledge graphs of policy comments that includes seven sentiments and five themes. The process of the sentiment knowledge graph constructed in this paper helps to more accurately understand the changes of online public opinion, and provides a theoretical basis for local governments to adjust the implementation of various policies. Apart from being the prototype of the automated sentiment knowledge graph system for policy comments, it can also be applied to other related hot topics.

KEYWORDS:

• sentiment knowledge graph
• Chinese government
• policy comments
• sentiment analysis
• text mining

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. China’s top ten major media websites: Sina Weibo, China government network, people’s daily, China Daily, Tencent, Xinhua, CCTV, Netease, today’s headlines, China net.

Additional information

Funding

This work was supported by the National Office for Philosophy and Social Sciences [17BTQ062].