{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/multimodal-emoji-prediction","title":"Multimodal Emoji Prediction","arxiv_id":"1803.02392","date":"2018-03-06","proceeding":"NAACL 2018 6","authors":["Francesco Barbieri","Miguel Ballesteros","Francesco Ronzano","Horacio Saggion"],"abstract":"Emojis are small images that are commonly included in social media text\nmessages. The combination of visual and textual content in the same message\nbuilds up a modern way of communication, that automatic systems are not used to\ndeal with. In this paper we extend recent advances in emoji prediction by\nputting forward a multimodal approach that is able to predict emojis in\nInstagram posts. Instagram posts are composed of pictures together with texts\nwhich sometimes include emojis. We show that these emojis can be predicted by\nusing the text, but also using the picture. Our main finding is that\nincorporating the two synergistic modalities, in a combined model, improves\naccuracy in an emoji prediction task. This result demonstrates that these two\nmodalities (text and images) encode different information on the use of emojis\nand therefore can complement each other.","url_abs":"http://arxiv.org/abs/1803.02392v2","url_pdf":"http://arxiv.org/pdf/1803.02392v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"multimodal-emoji-prediction","repo_url":"https://github.com/joonasrooben/NLP-text2emoji","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"prediction","task_name":"Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1803.02392","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}