Article Details

Abstract

With the rapid development of new quality productive forces and the digital economy, China's “low-altitude economy” industry is experiencing swift growth, accompanied by increasingly prominent public opinion risks and a widening information gap between industrial development and public perception. Weibo data, characterized by real-time interactivity and openness, contain substantial commercial value and social insight potential within their user behavior data. However, the outbreak of negative sentiment can influence public perception of the low-altitude economy and constrain its development, making the monitoring of public opinion on Weibo highly significant. Currently, sentiment analysis targeting the low-altitude economy remains insufficient, preventing relevant departments from rapidly identifying potential risks and taking timely governance measures. To address these challenges, this paper designs a Python-based visualization system for Weibo post data that crawls, processes, and analyzes content related to the low-altitude economy, including relevant topics and hot events. The system provides market demand insights and competitive product dynamic monitoring for low-altitude economy enterprises, tracks communication paths, popularity trends, and sentiment tendencies, and offers public opinion monitoring and decision-making references for regulatory authorities, thereby promoting the healthy development of the low-altitude industry.

Keywords

low-altitude economy; Weibo posts; visualization; data analysis; system design

References

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About the authors

Wu Simin (July 1993-), female, Han ethnicity, from Xinyi, Guangdong, teaching assistant, senior engineer, master's student, research direction: data mining and knowledge discovery.