Another observation is that memes can propagate globally through repackaging in different languages and that they can also be multilingual, blending different cultures. We further find that existing datasets mostly capture multi-class scenarios, which are not inclusive of the affective spectrum that memes can represent. One interesting finding is that many types of harmful memes are not really studied, e.g., such featuring self-harm and extremism, partly due to the lack of suitable datasets. Based on a systematic analysis of recent literature, we first propose a new typology of harmful memes, and then we highlight and summarize the relevant state of the art. With this in mind, here we offer a comprehensive survey with a focus on harmful memes. Yet, harmful content often combines multiple modalities, as in the case of memes, which are of particular interest due to their viral nature. Researchers have studied textual, visual, and audio content, but typically in isolation. You can also click related recommendations to view more background images in our huge database.The automatic identification of harmful content online is of major concern for social media platforms, policymakers, and society.
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