Multimodal Analysis of memes for sentiment extraction (2112.11850v1)

Abstract: Memes are one of the most ubiquitous forms of social media communication. The study and processing of memes, which are intrinsically multimedia, is a popular topic right now. The study presented in this research is based on the Memotion dataset, which involves categorising memes based on irony, comedy, motivation, and overall-sentiment. Three separate innovative transformer-based techniques have been developed, and their outcomes have been thoroughly reviewed.The best algorithm achieved a macro F1 score of 0.633 for humour classification, 0.55 for motivation classification, 0.61 for sarcasm classification, and 0.575 for overall sentiment of the meme out of all our techniques.