{"url":"/dataset/earnings-call","name":"Earnings Call","full_name":null,"description_markdown":"The Earning Calls dataset consists of processed earning conference calls data (text and audio). It can be used to predict financial risk from both textual and vocal features from conference calls.\n\nSource: [https://www.aclweb.org/anthology/P19-1038/](https://www.aclweb.org/anthology/P19-1038/)","description_withheld":null,"homepage":"https://github.com/GeminiLn/EarningsCall_Dataset","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/what-you-say-and-how-you-say-it-matters","title":"What You Say and How You Say It Matters: Predicting Stock Volatility Using Verbal and Vocal Cues","first_author":"Yu Qin","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Financial","url":"/datasets/modality/financial"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Earnings Call"],"data_loaders":[{"repo":"https://github.com/GeminiLn/EarningsCall_Dataset","url":"https://github.com/GeminiLn/EarningsCall_Dataset","frameworks":[]}],"num_papers_in_archive":9,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}