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Internet memes, in their ubiquitous spread across the digital landscape, have transformed into a potent communicative force. Their significance beckons keen interest from researchers and practitioners alike, necessitating a deep comprehension of their nuanced forms and functions. Recent studies have honed in on diverse facets of memes, particularly in detecting offensive material and discerning sarcasm, yet comprehensive instructional resources remain sparse. Addressing this void, our tutorial delivers an integrated framework for dissecting the complex humor of memes. It weaves together disciplines such as natural language processing, computer vision, and multimodal modeling, empowering participants to decode meanings, analyze sentiments, and identify offensive content within memes. Attendees will engage in hands-on exercises and observe demonstrations, tapping into established datasets and cutting-edge algorithms. This equips them with the expertise to navigate the intricacies of meme analysis and to contribute substantively to this dynamic domain. For more information, please check out our tutorial teaser video.
Hee et al. (Sun,) studied this question.