@inproceedings{sweed-shahaf-2021-catchphrase,
    title = "Catchphrase: Automatic Detection of Cultural References",
    author = "Sweed, Nir  and
      Shahaf, Dafna",
    editor = "Zong, Chengqing  and
      Xia, Fei  and
      Li, Wenjie  and
      Navigli, Roberto",
    booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.acl-short.1",
    doi = "10.18653/v1/2021.acl-short.1",
    pages = "1--7",
    abstract = "A snowclone is a customizable phrasal template that can be realized in multiple, instantly recognized variants. For example, {``}* is the new *'' (Orange is the new black, 40 is the new 30). Snowclones are extensively used in social media. In this paper, we study snowclones originating from pop-culture quotes; our goal is to automatically detect cultural references in text. We introduce a new, publicly available data set of pop-culture quotes and their corresponding snowclone usages and train models on them. We publish code for Catchphrase, an internet browser plugin to automatically detect and mark references in real-time, and examine its performance via a user study. Aside from assisting people to better comprehend cultural references, we hope that detecting snowclones can complement work on paraphrasing and help tackling long-standing questions in social science about the dynamics of information propagation.",
}