{"url":"/dataset/the-contextual-tv-dataset","name":"The Contextual TV Dataset","full_name":"CTV","description_markdown":"Using the Experience-Sampling Method (ESM), participants are asked to report TV consumption multiple times each day for a five week period. Through self-reported data, authors decrease uncertainty of exposure to content, and allow collection of non-trivial information, such as how much attention is paid to the TV. The data is structured to accommodate quantitative analyses, e.g. in the CARS community, and is publicly available under the name **Contextual TV (CTV)** dataset.\r\n\r\nSource: [Kristoffersen et al.](https://arxiv.org/pdf/1808.00337v2.pdf)\r\n\r\nImage source: [Kristoffersen et al.](https://arxiv.org/pdf/1808.00337v2.pdf)","description_withheld":null,"homepage":"https://vbn.aau.dk/da/datasets/contextual-tv-dataset","introduced_date":"2018-07-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-importance-of-context-when-recommending","title":"The Importance of Context When Recommending TV Content: Dataset and Algorithms","first_author":"Miklas S. Kristoffersen","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["The Contextual TV Dataset"],"data_loaders":[],"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."}