Emotional characteristics and time series analysis of Internet public opinion participants based on emotional feature words. (17th February 2020)

• Record Type: Journal Article
• Authors: Jia, Fengzhen; Chen, Chun-Chun
• Is Part Of: International journal of advanced robotic systems. Volume 17:Number 1(2020:Jan./Feb.)
• Publication Date: 2020-02-17
• Subjects: Network public opinion -- emotional classification dictionary -- weight calculation -- public opinion evolution; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881420904213
• Languages: English
• ISSNs: 1729-8806

Abstract

In recent years, with the rapid development and wide application of the Internet, it has become the main place for the generation and dissemination of public opinion. To grasp the information of network public opinion in a timely and comprehensive way can not only effectively prevent sudden network malignant events but also provide a reference for the scientific and democratic decision-making of government departments. Therefore, in view of the practical application needs, this article studies the emotional characteristics and the evolution of public opinion over time based on the emotional feature words of network public opinion participants. Firstly, the positive and negative emotional lexicon of HowNet emotional dictionary is used, and the commonly used emotional lexicon and expression symbols are added to the lexicon. At the same time, the polarity annotation method of Chinese emotional lexicon ontology is used to construct the emotional lexicon of this article. Secondly, considering other emotional polarity characteristics in the dictionary, an emotional tendency analysis model is proposed. In this article, emotional analysis is applied to the evolution analysis of network public opinion, and the change of network public opinion characteristics with time series is obtained. The simulation results show that the emotional dictionary constructed in this article and the proposed model of emotional orientation analysis can effectively analyze the emotional characteristics of network public opinion participants and apply emotional analysis to the evolution analysis of network public opinion, which can get the change of emotional characteristics of public opinion participants with time series.