Template-based generation of entertaining illustrations for news publication in social media using deep neural networks

Appropriate use of entertaining visuals, such as memes, increases engagement and shareability of the content. We introduce a novel approach to generate memes for news publications by templates which combines a generative language model for text generation and semantic image search based on joint embeddings for entertaining image selection. Finally, we have implemented it for Russian memes and assessed results by human evaluation.