@inproceedings{shoeb-etal-2019-emotag,
    title = "{E}mo{T}ag {--} Towards an Emotion-Based Analysis of Emojis",
    author = "Shoeb, Abu Awal Md  and
      Raji, Shahab  and
      de Melo, Gerard",
    editor = "Mitkov, Ruslan  and
      Angelova, Galia",
    booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)",
    month = sep,
    year = "2019",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd.",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/R19-1126/",
    doi = "10.26615/978-954-452-056-4_126",
    pages = "1094--1103",
    abstract = "Despite being a fairly recent phenomenon, emojis have quickly become ubiquitous. Besides their extensive use in social media, they are now also invoked in customer surveys and feedback forms. Hence, there is a need for techniques to understand their sentiment and emotion. In this work, we provide a method to quantify the emotional association of basic emotions such as anger, fear, joy, and sadness for a set of emojis. We collect and process a unique corpus of 20 million emoji-centric tweets, such that we can capture rich emoji semantics using a comparably small dataset. We evaluate the induced emotion profiles of emojis with regard to their ability to predict word affect intensities as well as sentiment scores."
}