Education Public opinion monitoring in the era of big data needs “gold rush in the sand” Currently, the Internet has entered the era of big data. It has about 4 characteristics listed here.
First and foremost, the data volume is huge. The ultra-large scale and growth of unstructured data account for 80% to 90% of the total data volume, which is 10 to 50 times faster than the growth of structured data;
Secondly; the big data Heterogeneity and diversity, such as pictures, videos, blogs, Weibo, WeChat, etc., is more important than the complexity of the data, and sometimes even small data in big data such as a Weibo has disruptive value;
Thirdly; the value density is low, and a large amount of irrelevant information needs to be panned in the sand;
And fourthly; the transmission speed is fast, so real-time analysis is required instead of batch analysis.
The Era of Big Data
In the era of big data, in the face of such massive and fast information, purely manual monitoring of the Internet is no longer feasible. Software has become the engine of education public opinion monitoring and analysis under the big data environment.
For example, our road map for public opinion monitoring of educational networks is a double-funnel model. First, we must conduct a “gold rush”, that is, first collect all information, analyze and filter information related to ourselves, and then analyze the data in an orderly manner.
Monitoring public opinion can set up some key words, we must first associated with their bodies, may include competitors or cooperation partners, and then to put a region or across the country to collect. After collecting all the “sands”, we began to aggregate information to determine which ones are related to education, which ones are related to the region, and which ones are related to ourselves.
After collecting and filtering this information, the next step is to refine and analyze, including communication statistics and analysis (media analysis, main body communication distribution, communication path analysis, communication source tracking), sensitive (negative) public opinion research and judgment, and public opinion information dissemination Trend analysis, predict the future trend of public opinion information collected.
On this basis, a public opinion briefing is generated. The public opinion briefing is automatically generated by the system. The public opinion monitored at this stage is counted and analyzed on a daily or weekly basis, including public opinion distribution, hot public opinion ranking, negative public opinion analysis, and positive public opinion ranking.
Topics related to Era of Big Data
- Is big data dying?
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The function of educational public opinion monitoring software is embodied in the “gold rush in the sand”. First of all, it must be comprehensive, fast and accurate, so that the public opinion monitored is valuable. Second, public opinion analysis software and tools must be ready.
In addition, public opinion analysis is a systematic project, which requires software tools, public opinion analysis experts, and specialized organizations to ensure that public opinion monitoring can be effective. Finally, Public Opinion Monitoring in the Era of Big Data Trends is available on the related posts.