{
  "fetched_at": "2026-10-19T19:22:17Z",
  "source_url": "https://www.kaggle.com/competitions/datasciencediku/data",
  "pages": [
    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
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      "hasIsPublished": false,
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    {
      "name": "data-description",
      "content": "You're allowed to use the following sources of data:\n\n- https://github.com/several27/FakeNewsCorpus\n- Any data you mined during the first phase of the project \n\nSince these two datasets (and the data you mined) have different label sets, it will be up to you to decide how to best bin them into 'True' and 'False' classes. The final (hidden) test set will only have 'REAL' and 'FAKE' labels. \n\nBelow you can download the test set (from an unknown source), for which the labels have been removed. You're then supposed to submit predictions for this test set in the form of: ID,PREDICTION.\n\nThe predictions file that you submit for the test set should have the following header: \"id,label\". \n\nThe liar dataset ( https://www.cs.ucsb.edu/~william/data/liar_dataset.zip) will be used for cross-domain testing. ",
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      "postTitle": "",
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    },
    {
      "name": "Final Project Leaderboard",
      "content": "This is the leaderboard for the Datascience course final project. Here you can submit your predictions for the test set and it will be evaluated against the gold labels. Your teams' ranking will be based on the accuracy of your model on this test set. Each team is only allowed three submissions per day and thirty in total.  ",
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      "hasIsPublished": false,
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    },
    {
      "name": "Evaluation",
      "content": "<p>The evaluation metric for this competition is accuracy. This will be calculated as number of **correct predictions / total number of predictions**. </p>\n\n<h2>Submission Format</h2>\n<p><strong>For every sample in the in the test set</strong>, submission files should contain two columns: Id and Label. Labels can either be **FAKE** or **REAL** . </p>\n<p>The file should contain a header of the following format:</p>\n<pre>id,label</pre>",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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      "mimeType": "",
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    },
    {
      "name": "Timeline",
      "content": "The deadline will be on the 14/06/2019 at 11.59 p.m..",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Prizes",
      "content": "Course grades. ",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Kernels Requirements",
      "content": "None.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
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    },
    {
      "name": "Description",
      "content": "The goal of this project is to work toward actually creating a Fake News predictor. This will build on the work you have done in the Milestone, combined with the topics covered in the lectures in this second block of the course.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
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    }
  ]
}