Big Data Analysis of Video Index Popularity and Public Emotion Based on Python

With the development of network service infrastructure and the Internet itself, people can watch various videos online or download in real time. For these videos, there are some key information, such as video index popularity, comment public opinion, etc. Under this background, in order to achieve the purpose of analyzing the video index popularity and public opinion of the video, this article will try to use the wheels related to Python language and Ecosystem, to realize big data analysis of video index popularity and public opinion. The specific research method is that the first step is the preparation and acquisition of data, which is realized by using web crawler technology. Taking “Fast and Furious 9” as an example, to capture the There are four sets of data on the Qiyi Index website: content popularity trend, Qisou index, comment core views, and core view trends; the second step is data analysis, visualization (choose appropriate charts), analysis and summary to draw conclusions, etc. After repeated execution of updating data and analysis and display without interruption, the relevant data and charts will change in real time every time it is updated. It can help people realize realtime analysis and conclusion output of video index popularity and public opinion big data.