{"url":"/dataset/ntpairs","name":"NTPairs","full_name":"News-Tweet Paired Dataset","description_markdown":"The **NTPairs** dataset consists of the pairs of news articles and their corresponding tweets that were published by eight media outlets in 2018. The eight outlets were selected to consider diverse outlets, which employ a different editing style for news sharing, in terms of publishing channels and political leaning.\n\nSource: [https://github.com/bywords/NTPairs](https://github.com/bywords/NTPairs)\nImage Source: [https://github.com/bywords/NTPairs](https://github.com/bywords/NTPairs)","description_withheld":null,"homepage":"https://github.com/bywords/NTPairs","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/understanding-effects-of-editing-tweets-for","title":"How-to Present News on Social Media: A Causal Analysis of Editing News Headlines for Boosting User Engagement","first_author":"Kunwoo Park","url":null},"license":null,"modalities":[],"tasks":[{"name":"Causal Inference","url":"/task/causal-inference","datasets_with_task":"/datasets/task/causal-inference"}],"languages":[],"variants":["NTPairs"],"data_loaders":[{"repo":"https://github.com/bywords/NTPairs","url":"https://github.com/bywords/NTPairs","frameworks":[]}],"num_papers_in_archive":1,"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."}