Abstract: Public opinion evaluation is becoming increasingly significant in infrastructure project assessment. The inefficiencies of conventional evaluation approaches can be improved with social media analysis. Posts about infrastructure projects on social media provide a large amount of data for assessing public opinion. This study proposed a public opinion evaluation framework with machine learning algorithms, including sentiment analysis and topic modelling. We selected the United Kingdom railway project, High Speed 2, as the case study. The sentiment analysis showed that around 53% to 63% of tweets expressed a negative sentiment, suggesting the public may have an overall negative perception of the project. Topic modelling with text corpora showed key topics of public opinion. The proposed framework demonstrates the feasibility of using supervised machine learning to evaluate public opinion on infrastructure projects, as the framework can save time and cost. Furthermore, assessment results can aid policymakers and managers in decision-making.