Abstract: Improving screening and addressing terrorist information in social media becomes a critical topic of research． Our study uses data crawlers and screening analysis to classify different terrorist information． Through scrappy framework and genism tool pack，we obtained the relevant data from four datasets． After constructing a LDA ( Latent Dirichlet Allocation) theme model，we then classified several themes in four different area that played major roles in propagating terrorism，and investigated the interconnected relationship between these themes． The experiment indicates that the model can effectively distinguish different themes of terrorism information and the role it played in propagation．

Key words: terrorism, big data, web crawler, theme analysis