{
  "fetched_at": "2026-10-24T09:14:40Z",
  "source_url": "https://www.kaggle.com/competitions/22fall-micro-course-4-w2v-d2v/data",
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      "name": "Description",
      "content": "This is the Kaggle task for Micro Course-4, Twitter Sentiment Analysis\n\n## Objectives\nReview the basic TF-IDF and SVM model.\nCompare various word embedding methods (e.g. TF-IDF, w2v, d2v).\nTry to use what you learned in real world problem.\n\n## Task Description\nPlease try to detect hate speech in the given tweets with different word embedding methods.\n\n## Acknowledgements\nSample Code:\nhttps://colab.research.google.com/drive/1uB8FkS24l5y6-N34WTN61y59bRYMRiGP?usp=sharing\nPlease remember not to share the codes to the public.\n\nLast but not least,\nthanks for another competition holder, Haren Lin, for providing the kaggle draft. \n\nDemo Sites\n• Word Embedding\n– https://projector.tensorflow.org/\n• Sentiment Analysis\n– https://ai.baidu.com/tech/nlp_apply/sentiment_classify\n– https://text2data.com/Demo\n• Text Generator\n– https://app.inferkit.com/demo\n• Language Understanding\n– https://www.ibm.com/demos/live/natural-languageunderstanding/self-service/home\n• Question & Answering\n– https://ckip.iis.sinica.edu.tw/service/qademo/",
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      "name": "Evaluation",
      "content": "The evaluation metric for the competition is Macro F-Score, rather then Accuracy.\n",
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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!",
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