Irony is a form of figurative language, which is often used to make fun of an entity. We employ paragraph vector to capture syntactic and semantic features of the figurative language to subsequently detect satiric and ironic content in a given text using data mining. We extract psycholinguistic features with the help of a tool called Linguistic Inquiry Word Count. In order to extract useful insights of what constitutes figurative language, we combined syntactic, semantic, and psycholinguistic features together. We demonstrated the effectiveness of the proposed methodology on two satiric news datasets and one ironic customer review dataset. The proposed approach outperformed on the state of the art results.