Spatio-temporal heterogeneity and topic evolution trends of public carbon neutrality attention in China

Abstract

This study examines the spatiotemporal evolution and regional disparities in public attention to carbon neutrality under the ”dual carbo” goals to inform more effective policy design. Departing from traditional single-dimensional approaches, it introduces an interdisciplinary analytical framework – spatiotemporal measurement, sentiment analysis, and topic evolution – to capture dynamic shifts in public discourse on carbon neutrality in China, based on 119,000 Sina Weibo posts (2018–2023). The study makes the following key contributions: (1) It applies Dagum Gini coefficient decomposition and kernel density estimation to identify regional attention patterns, revealing higher attention in central regions, lower levels in the west, and evident ”multi-polarization” within regions; (2) It develops a CNN-BiLSTM-Attention model for sentiment classification, demonstrating that the emotional polarity of topics such as ”low-carbon lifestyle” closely aligns with policy promulgation frequency; (3) It employs the VSTC clustering model to examine topic evolution, identifying four major thematic trajectories: individual environmental behavior, green economy, global governance, and sustainable development. These reflect a progression from micro-level personal actions to macro-level policies and industrial practices. Overall, this study provides a solid quantitative basis for optimizing carbon neutrality policies in China.