Research on Sentiment Tendency and Evolution of Public Opinions in Social Networks of Smart City

Yanni Liu,Yuwei Chen,Dongsheng Liu

doi:10.1155/2020/9789431

Abstract

With the rapid development of mobile Internet, the social network has become an important platform for users to receive, release, and disseminate information. In order to get more valuable information and implement effective supervision on public opinions, it is necessary to study the public opinions, sentiment tendency, and the evolution of the hot events in social networks of a smart city. In view of social networks’ characteristics such as short text, rich topics, diverse sentiments, and timeliness, this paper conducts text modeling with words co-occurrence based on the topic model. Besides, the sentiment computing and the time factor are incorporated to construct the dynamic topic-sentiment mixture model (TSTS). Then, four hot events were randomly selected from the microblog as datasets to evaluate the TSTS model in terms of topic feature extraction, sentiment analysis, and time change. The results show that the TSTS model is better than the traditional models in topic extraction and sentiment analysis. Meanwhile, by fitting the time curve of hot events, the change rules of comments in the social network is obtained.

Highlights

With the wide application of the Internet technology, the Internet has gradually transformed to the dynamic platform for information sharing and interactive communication. e 43rd statistical report indicated that China had 854 million Internet users, and 99.1 percent of them access the Internet via mobile phones [1]
Social networks of a smart city have become the mainstream platform for information exchange and opinion expression. e users are the receivers of information, and the creators to publish text comments in social networks. e hot events of public opinion refer that personal opinions are released on upcoming or already happened events by online communication tools and network platforms [2]. e spread of public opinion will snowball and expand by social networks, and emergent events may develop in an uncontrollable direction
The above research cannot meet the needs of online public opinion supervision, and the monitoring and management of hot events in social networks of a smart city need to implement quantitative judgment

Summary

Introduction

With the wide application of the Internet technology, the Internet has gradually transformed to the dynamic platform for information sharing and interactive communication. e 43rd statistical report indicated that China had 854 million Internet users, and 99.1 percent of them access the Internet via mobile phones [1]. Social networks of a smart city have become the mainstream platform for information exchange and opinion expression. E hot events of public opinion refer that personal opinions are released on upcoming or already happened events by online communication tools and network platforms [2]. Previous research has been studied from the qualitative aspects, such as the evolution mechanism of public opinion, information element classification, and influence judgment. The above research cannot meet the needs of online public opinion supervision, and the monitoring and management of hot events in social networks of a smart city need to implement quantitative judgment. For public opinion monitoring and management, Steyvers and Griffiths [4] proposed a topic model for public opinion detection in the social network. Kim et al [8] introduced the sentiment scoring based on topics through the n-gram LDA

Results

Discussion

Conclusion