Open AccessComprehensiveness, Preciseness and Interconnectedness: How to Evaluate International Public Opinion Based on Cross-media Data Mining on the Internet
Author(s) -
Tianqi Deng,
Xiaotian Hou,
Yumo Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1944/1/012003
Subject(s) - popularity , big data , computer science , data science , cyberspace , public opinion , the internet , sentiment analysis , china , thematic analysis , focus (optics) , world wide web , data mining , political science , artificial intelligence , sociology , politics , qualitative research , social science , physics , optics , law
With emerging new media technologies, the analytic focus of research on international public opinions has switched from single content form, such as text, audio, image or video into multiple forms of media integrated together in cyberspace or in physical space. The depth and frequency of monitoring international public opinion on topics related to China are improving rapidly. This paper pinpoints the inadequacies of current monitoring activities and puts forward ways to analyze international public opinions on topics related to China based on technologies, such as web indexing, deep learning and data mining. Thematic discovery based on big data analytics, real-time surveillance and monitoring of trending topics, intelligent prediction of popularity, intelligent analysis of emotional valence, etc. can effectively support the establishment of a system using multimedia data to monitor and analyze international public opinion.