Semantic search for public opinions on urban affairs: A probabilistic topic modeling-based approach

•The explosion of online user-generated content (UGC) and the development of big data analysis provide a new opportunity and challenge to understand and respond to public opinions in the G2C e-government context.•We proposed an approach based on the latent Dirichlet allocation (LDA) and designed a practical system to provide users with satisfying searching results and the longitudinal changing curves of related topics.•Municipal administrators could better understand citizens’ online comments based on the proposed semantic search approach and could improve their decision-making process by considering public opinions.