Ecological restoration is a complex process characterized by dynamic, bidirectional feedbacks within socialecological systems. Public attitudes, as a critical nexus between natural and social subsystems, have rarely been quantitatively examined in terms of their impact on restoration performance. Taking the Yellow River Basin as a case study, this study employed the Chinese-RoBERTa-wwm-ext model to analyze social media data and characterize public attitudes toward ecological conservation. Furthermore, a Latent Dirichlet Allocation model based on Term Frequency-Inverse Document Frequency was used to perform a fine-grained analysis of sentiments in public posts. A coupling coordination model was utilized to explore the relationship between ecological restoration effectiveness (ERE) and public enthusiasm for ecological conservation (PEC). Additionally, the XGBoost-SHAP model and SOM-K-means algorithm were used to develop differentiated governance strategies. The results showed that ERE and PEC exhibited a fluctuating upward trend, with significant spatial gradients. The middle reaches consistently exhibited the highest coordination levels. Overall, 94.59% of cities displayed a benign synergistic relationship between ERE and PEC. However, ecological governance in fragile upstream areas still faces substantial challenges. Meteorological disasters associated with low vegetation cover and arid climates have elicited strong public dissatisfaction. The study revealed that population density and educational attainment are the primary drivers shaping PEC. A targeted governance framework based on spatial heterogeneity and threshold effects is therefore proposed to mobilize endogenous social drivers of ecological restoration. By integrating social sensing methods to support environmental recovery, this study provides a novel perspective for advancing regional sustainability and the modernization of global ecological governance.