{"url":"/dataset/kickstarter","name":"kickstarter","full_name":"Funding Successful Projects on Kickstarter","description_markdown":"Kickstarter is a community of more than 10 million people comprising of creative, tech enthusiasts who help in bringing creative project to life. Till now, more than $3 billion dollars have been contributed by the members in fueling creative projects. The projects can be literally anything – a device, a game, an app, a film etc.\r\n\r\nKickstarter works on all or nothing basis i.e if a project doesn’t meet it goal, the project owner gets nothing. For example: if a projects’s goal is \\$500. Even if it gets funded till \\$499, the project won’t be a success.\r\n\r\nRecently, Kickstarter released its public data repository to allow researchers and enthusiasts like us to help them solve a problem. Will a project get fully funded ?","description_withheld":null,"homepage":"https://www.kaggle.com/datasets/codename007/funding-successful-projects","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Tabular","url":"/datasets/modality/tabular"}],"tasks":[{"name":"Binary Classification","url":"/task/binary-classification","datasets_with_task":"/datasets/task/binary-classification"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["kickstarter"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/binary-classification-on-kickstarter","task":"Binary Classification","dataset_variant":"kickstarter","rows":4,"metrics":["AUROC"],"first_row_in_archive_order":{"model":"Trompt + OpenAI embedding","paper":"/paper/pytorch-frame-a-modular-framework-for-multi","metrics":{"AUROC":"0.81"},"code_links":[{"title":"pyg-team/pytorch-frame","url":"https://github.com/pyg-team/pytorch-frame"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/pytorch-frame-a-modular-framework-for-multi","title":"PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning","date":"2024-03-31","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/benchmarking-multimodal-automl-for-tabular","title":"Benchmarking Multimodal AutoML for Tabular Data with Text Fields","date":"2021-11-04","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":4,"samples_ran":4,"samples_unverified":0,"pointer_only_for_licence":2,"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."}