Spatio-Temporal Evolution Analysis of AIGC Public Sentiment Based on Bi-LSTM-Attention Algorithm

This study proposes a spatio-temporal evolution analysis framework based on Bi-LSTM-Attention to decipher the patterns of public sentiment dissemination regarding AIGC (Artificial Intelligence Generated Content) in China. By scraping 8,765 data points from Sina Weibo between 2017 and 2025, and integrating public engagement index and sentiment index, the research unveils the spatio-temporal characteristics of AIGC-related public sentiment. Temporal analysis indicates that discussions on the technology have experienced exponential growth since 2023, peaking in 2025. Spatial analysis explores the correlation between regional economic levels and technology penetration. The findings offer methodological insights for technology governance.