Design and Implementation of a Microblog Public Opinion Visualization System Based on Flask and ECharts

Authors

  • Yun Liu
  • Dong Xiao

DOI:

https://doi.org/10.62051/nq8zkq20

Keywords:

Weibo public opinion Analysis, Data Visualization, Sentiment Analysis.

Abstract

Conducting public opinion analysis on Weibo data is of significant importance to decision-making processes in government, enterprises, and personal contexts. This paper presents the design and implementation of a real-time microblog public opinion visualization system based on Flask and ECharts. The system aims at effectively monitoring Weibo data in real time, performing sentiment analysis, and trend prediction.The system adopts a B/S architecture, employing distributed web crawling techniques to efficiently gather Weibo data. For sentiment analysis, the SnowNLP library is utilized. On the frontend, the ECharts charting library dynamically displays the sentiment data, offering users an intuitive interface and interactive experience.In designing the system, considerations have been given to data processing efficiency, real-time capabilities, scalability, and data security to cater to the diverse needs of different users. By integrating these technologies, the system provides comprehensive insights into the prevailing sentiments, trending topics, and patterns within the vast volume of Weibo content.

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References

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Published

20-06-2024

How to Cite

“Design and Implementation of a Microblog Public Opinion Visualization System Based on Flask and ECharts” (2024) Transactions on Computer Science and Intelligent Systems Research, 4, pp. 97–104. doi:10.62051/nq8zkq20.

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