@inproceedings{shardlow-etal-2025-exploring,
    title = "Exploring Supervised Approaches to the Detection of Anthropomorphic Language in the Reporting of {NLP} Venues",
    author = "Shardlow, Matthew  and
      Williams, Ashley  and
      Roadhouse, Charlie  and
      Ventirozos, Filippos  and
      Przyby{\l}a, Piotr",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingestion-acl-25/2025.findings-acl.926/",
    pages = "18010--18022",
    ISBN = "979-8-89176-256-5",
    abstract = "We investigate the prevalence of anthropomorphic language in the reporting of AI technology, focussed on NLP and LLMs. We undertake a corpus annotation focussing on one year of ACL long-paper abstracts and news articles from the same period. We find that 74{\%} of ACL abstracts and 88{\%} of news articles contain some form of anthropomorphic description of AI technology. Further, we train a regression classifier based on BERT, demonstrating that we can automatically label abstracts for their degree of anthropomorphism based on our corpus. We conclude by applying this labelling process to abstracts available in the entire history of the ACL Anthology and reporting on diachronic and inter-venue findings, showing that the degree of anthropomorphism is increasing at all examined venues over time."
}