@inproceedings{tian-etal-2017-facebook,
    title = "{F}acebook sentiment: Reactions and Emojis",
    author = "Tian, Ye  and
      Galery, Thiago  and
      Dulcinati, Giulio  and
      Molimpakis, Emilia  and
      Sun, Chao",
    booktitle = "Proceedings of the Fifth International Workshop on Natural Language Processing for Social Media",
    month = apr,
    year = "2017",
    address = "Valencia, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W17-1102",
    doi = "10.18653/v1/W17-1102",
    pages = "11--16",
    abstract = "Emojis are used frequently in social media. A widely assumed view is that emojis express the emotional state of the user, which has led to research focusing on the expressiveness of emojis independent from the linguistic context. We argue that emojis and the linguistic texts can modify the meaning of each other. The overall communicated meaning is not a simple sum of the two channels. In order to study the meaning interplay, we need data indicating the overall sentiment of the entire message as well as the sentiment of the emojis stand-alone. We propose that Facebook Reactions are a good data source for such a purpose. FB reactions (e.g. {``}Love{''} and {``}Angry{''}) indicate the readers{'} overall sentiment, against which we can investigate the types of emojis used the comments under different reaction profiles. We present a data set of 21,000 FB posts (57 million reactions and 8 million comments) from public media pages across four countries.",
}