Data Mining and Big Data in Social Media Public Opinion Monitoring
Dandan Zhang · Media and Communication Research · 2023
With the popularization of the Internet, social media has become one of the most common communication methods, and a large amount of information is generated on social media at every moment. These pieces of information contain a large amount of public opinion data, making social media an important source of public opinion. In the application of social media public opinion monitoring, utilizing Big Data (BD) technology to process and mine massive data from social media has become an important means of public opinion monitoring. At present, there are mature technologies and tools in this field, but further research is needed for multilingual and multicultural Data Mining (DM), as well as BD analysis and linkage prediction of micro and macro public opinion. This article uses DM and BD analysis to monitor public opinion on social media, and verifies it by conducting keyword mining on corresponding web pages in the medical, transportation, education, public security, and military industries. It can be concluded that the number of keywords captured by DM and BD analysis methods in healthcare, transportation, education, public security, and military is 980, 830, 789, 445, and 657, respectively. The number of keywords captured by traditional methods is 670, 545, 489, 245, and 557. From this, it can be seen that through DM and BD analysis techniques, valuable public opinion information can be extracted from social media data, achieving the goal of real-time tracking of social public opinion and predicting the development of micro and macro public opinion.