With the rapid development of information technologies, the implementation of visual content has become a complementary component of social discourse, particularly in the media and news sectors. In this respect, it is increasingly important to pay huge attention to media literacy and relevant information processing. Sarcasm, one of the most widely used language choices in social discourse, can easily be a part of any media or news article. Sarcastic remarks are used for numerous reasons, namely, to indirectly express contempt, pretend an attitude, mock a situation or a person, or perhaps, they are more creative solutions to anger-provoking situations. The aim of the present research is to detect sarcastic messages in media and news articles through the multimodal markers of the discourse. The dataset analyzed to achieve the above-mentioned goal is derived from American and British media and news platforms Politico, The Guardian, and The Sun.