Information on social media comprises of various modalities such as textual, visual and audio. NLP and Computer Vision communities often leverage only one prominent modality in isolation to study social media. However, the computational processing of Internet memes needs a hybrid approach. The growing ubiquity of Internet memes on social media platforms such as Facebook, Instagram, and Twitter further suggests that we can not ignore such multimodal content anymore. The objective of this research is to automatic processing of Internet memes. We primarily focus on three subtasks: sentiment (positive, negative, and neutral) analysis of memes, overall emotion (humour, sarcasm, offensive, and motivational) classification of memes, and classifying intensity of meme emotion.