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license: apache-2.0 |
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dataset_info: |
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splits: |
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- name: train |
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num_bytes: 100367999 |
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num_examples: 84437 |
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- name: validation |
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num_bytes: 5243405 |
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num_examples: 4401 |
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download_size: 41596430 |
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dataset_size: 105611404 |
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language: |
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- en |
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size_categories: |
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- 1M<n<10M |
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tags: |
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- misinformation |
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- text |
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pretty_name: Misinformation Detection Dataset |
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Modalities: |
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- Text |
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--- |
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# Misinfo Detection Dataset |
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## Dataset Description |
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- **Homepage:** https://yxguan.github.io/ComplexData-Misinfo-test1/ |
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- **Repository:** https://github.com/ComplexData-MILA/misinfo-datasets |
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- **Paper:** https://arxiv.org/abs/2104.06952 |
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### Dataset Summary |
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Misinformation is a challenging societal issue, and mitigating solutions are difficult to create due to data deficiencies. To address this problem, we have curated the largest collection of (mis)information datasets in the literature, totaling 72. From these, we evaluated the quality of all of the 32 datasets that consist of statements or claims. If you would like to contribute a novel dataset or report any issues, please email us or visit our GitHub. |
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Please refer to our [paper](https://arxiv.org/abs/2104.06952) for further details. |
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### Team |
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This dataset is made available by [Complex Data Lab](https://complexdatalabmcgill.github.io/), a group composed of researchers from University of Montreal and McGill University. |
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The lab is led by [Dr. Reihaneh Rabbany](https://complexdatalabmcgill.github.io/team/reihaneh+rabbany) and [Dr. Jean-François Godbout |
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](https://jf-godbout.github.io/) |
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