Lakhasly

Hate speech consists of types of content (e.g. text, audio, image) that express derogatory sentiments and hate against certain people or groups of individuals.The internet, particularly social media and microblogging sites, have become an increasingly popular platform for expressing ideas and opinions. A substantial proportion of this kind of content is presented in different modalities (e.g. text, image, video).Hate speech is prevalent in both offline and online media.

Hate speech consists of types of content (e.g.
text, audio, image) that express derogatory
sentiments and hate against certain people or
groups of individuals. The internet, particularly
social media and microblogging sites, have become an increasingly popular platform for expressing ideas and opinions. Hate speech is
prevalent in both offline and online media. A
substantial proportion of this kind of content
is presented in different modalities (e.g. text,
image, video). Taking into account that hate
speech spreads quickly during political events,
we present a novel multimodal dataset composed of 5680 text-image pairs of tweets data
related to the Russia-Ukraine war and annotated with a binary class: ”hate” or ”no-hate”
The baseline results show that multimodal resources are relevant to leverage the hateful information from different types of data. The
baselines and dataset provided in this paper
may boost researchers in direction of multimodal hate speech, mainly during serious conflicts such as war contexts.