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The dataset for training and evaluating multimodal toxic memes detection models. Contains images, extracted texts and toxicity labels. Images are collected from popular Russian Telegram channels and labelled with respect to Facebook Community Standards.
binary classification, hate speech, social media, multimodal classification, memes, toxic content, image and text classification, multimodality
binary classification, hate speech, social media, multimodal classification, memes, toxic content, image and text classification, multimodality
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 10 | |
| downloads | 1 |

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