{
  "fetched_at": "2026-10-20T10:38:03Z",
  "source_url": "https://www.kaggle.com/competitions/emailsentimentanalysis/data",
  "pages": [
    {
      "name": "data-description",
      "content": "For a given text of the letter (or a chain of correspondence?) To determine the emotional background (positive, negative, constructive, critical, etc.).\n5-10 examples with \"marking\" of emotional coloring are given.\nData uploaded to kaggle in-class competition: https://www.kaggle.com/c/emailsentimentanalysis.\nYou need to determine the emotional background for a given letter (or a set of letters?).\nTesting will be performed on prepared sample letters, which will be provided to the teams directly during the final presentation. The results will depend on:\n1) quality of the sentiment predicted by the model for given emails (during the presentation); metric - MAE (1 - Very negative, …, 5 - Very positive)\n2) idea behind the proposed method\n3) quality of the presentation\n",
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    {
      "name": "Description",
      "content": "**Email Sentiment Analysis**\n\nFor a given text of the letter determine the emotional background (positive, negative, neutral, etc.).\n5 examples with sentiment labeling are given.\n",
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      "postTitle": "",
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    {
      "name": "Evaluation",
      "content": "Evaluation metric - MAE. Sentiments were mapped to corresponding numbers: 1 - Very negative, …, 5 - Very positive (see Data section).\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "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!",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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}