{
  "id": 144097,
  "title": "Good Papers on Toxic Comment Classification",
  "url": "/competitions/jigsaw-multilingual-toxic-comment-classification/discussion/144097",
  "author_name": "",
  "post_date": "2020-04-17T15:49:30.514395800Z",
  "votes": 20,
  "comment_count": 4,
  "views": 0,
  "content": "<ul>\n<li><p>Detecting and Classifying Toxic comments\n<a href=\"https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6837517.pdf\">https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6837517.pdf</a></p></li>\n<li><p>Exploring Deep Learning in Combating Internet Toxicity\n<a href=\"https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6909170.pdf\">https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6909170.pdf</a></p></li>\n<li><p>Toxic Comment Classification Using Neural Networks and Machine Learning\n<a href=\"https://iarjset.com/wp-content/uploads/2018/10/IARJSET.2018.597.pdf\">https://iarjset.com/wp-content/uploads/2018/10/IARJSET.2018.597.pdf</a></p></li>\n<li><p>Convolutional Neural Networks for Toxic Comment Classification\n<a href=\"https://arxiv.org/pdf/1802.09957.pdf\">https://arxiv.org/pdf/1802.09957.pdf</a></p></li>\n<li><p>A Machine Learning Approach to Comment Toxicity Classification\n<a href=\"https://arxiv.org/ftp/arxiv/papers/1903/1903.06765.pdf\">https://arxiv.org/ftp/arxiv/papers/1903/1903.06765.pdf</a></p></li>\n<li><p>Adversarial Text Generation for Google’s Perspective \n<a href=\"https://www.nyit.edu/files/engineering/SOECS_REU2018_PosterPresentation_AdversarialTextGenerationForGooglePerspective.pdf\">https://www.nyit.edu/files/engineering/SOECS_REU2018_PosterPresentation_AdversarialTextGenerationForGooglePerspective.pdf</a></p></li>\n<li><p>Content Moderation Across Multiple Platforms with Capsule Networks and Co-Training\n<a href=\"http://precog.iiitd.edu.in/Publications_files/Vani_Agarwal_Masters_Thesis.pdf\">http://precog.iiitd.edu.in/Publications_files/Vani_Agarwal_Masters_Thesis.pdf</a></p></li>\n</ul>",
  "messages": [
    {
      "id": "811110",
      "postDate": "04/17/2020 15:49:30",
      "content": "<ul>\n<li><p>Detecting and Classifying Toxic comments\n<a href=\"https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6837517.pdf\">https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6837517.pdf</a></p></li>\n<li><p>Exploring Deep Learning in Combating Internet Toxicity\n<a href=\"https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6909170.pdf\">https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6909170.pdf</a></p></li>\n<li><p>Toxic Comment Classification Using Neural Networks and Machine Learning\n<a href=\"https://iarjset.com/wp-content/uploads/2018/10/IARJSET.2018.597.pdf\">https://iarjset.com/wp-content/uploads/2018/10/IARJSET.2018.597.pdf</a></p></li>\n<li><p>Convolutional Neural Networks for Toxic Comment Classification\n<a href=\"https://arxiv.org/pdf/1802.09957.pdf\">https://arxiv.org/pdf/1802.09957.pdf</a></p></li>\n<li><p>A Machine Learning Approach to Comment Toxicity Classification\n<a href=\"https://arxiv.org/ftp/arxiv/papers/1903/1903.06765.pdf\">https://arxiv.org/ftp/arxiv/papers/1903/1903.06765.pdf</a></p></li>\n<li><p>Adversarial Text Generation for Google’s Perspective \n<a href=\"https://www.nyit.edu/files/engineering/SOECS_REU2018_PosterPresentation_AdversarialTextGenerationForGooglePerspective.pdf\">https://www.nyit.edu/files/engineering/SOECS_REU2018_PosterPresentation_AdversarialTextGenerationForGooglePerspective.pdf</a></p></li>\n<li><p>Content Moderation Across Multiple Platforms with Capsule Networks and Co-Training\n<a href=\"http://precog.iiitd.edu.in/Publications_files/Vani_Agarwal_Masters_Thesis.pdf\">http://precog.iiitd.edu.in/Publications_files/Vani_Agarwal_Masters_Thesis.pdf</a></p></li>\n</ul>",
      "rawMarkdown": "Detecting and Classifying Toxic comments\nhttps://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6837517.pdf\n\n- Exploring Deep Learning in Combating Internet Toxicity\nhttps://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6909170.pdf\n\n- Toxic Comment Classification Using Neural Networks and Machine Learning\nhttps://iarjset.com/wp-content/uploads/2018/10/IARJSET.2018.597.pdf\n\n- Convolutional Neural Networks for Toxic Comment Classification\nhttps://arxiv.org/pdf/1802.09957.pdf\n\n- A Machine Learning Approach to Comment Toxicity Classification\nhttps://arxiv.org/ftp/arxiv/papers/1903/1903.06765.pdf\n\n- Adversarial Text Generation for Google’s Perspective \nhttps://www.nyit.edu/files/engineering/SOECS_REU2018_PosterPresentation_AdversarialTextGenerationForGooglePerspective.pdf\n\n- Content Moderation Across Multiple Platforms with Capsule Networks and Co-Training\nhttp://precog.iiitd.edu.in/Publications_files/Vani_Agarwal_Masters_Thesis.pdf",
      "votes": null
    },
    {
      "id": "813641",
      "postDate": "04/19/2020 20:32:03",
      "content": "<p>Thanks!</p>",
      "rawMarkdown": "Thanks!",
      "votes": null
    },
    {
      "id": "814724",
      "postDate": "04/20/2020 22:33:10",
      "content": "<p>Great ,Thanks for sharing!</p>",
      "rawMarkdown": "Great ,Thanks for sharing!",
      "votes": null
    },
    {
      "id": "815010",
      "postDate": "04/21/2020 07:27:10",
      "content": "<p>Thanks 🤜🏼</p>",
      "rawMarkdown": "Thanks 🤜🏼",
      "votes": null
    },
    {
      "id": "1991976",
      "postDate": "10/17/2022 13:29:33",
      "content": "<p>Thanks a lot.</p>",
      "rawMarkdown": "Thanks a lot.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1991976,
      "author_name": "basmarg",
      "author_url": "",
      "post_date": "10/17/2022 13:29:33",
      "content": "<p>Thanks a lot.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 813641,
      "author_name": "hikkariprogrammer",
      "author_url": "",
      "post_date": "04/19/2020 20:32:03",
      "content": "<p>Thanks!</p>",
      "votes": null,
      "replies": [
        {
          "id": 815010,
          "author_name": "jpnewton",
          "author_url": "",
          "post_date": "04/21/2020 07:27:10",
          "content": "<p>Thanks 🤜🏼</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 814724,
      "author_name": "mielek",
      "author_url": "",
      "post_date": "04/20/2020 22:33:10",
      "content": "<p>Great ,Thanks for sharing!</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "811110": "Detecting and Classifying Toxic comments\nhttps://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6837517.pdf\n\n- Exploring Deep Learning in Combating Internet Toxicity\nhttps://web.stanford.edu/class/archive/cs/cs224n/cs224n.1184/reports/6909170.pdf\n\n- Toxic Comment Classification Using Neural Networks and Machine Learning\nhttps://iarjset.com/wp-content/uploads/2018/10/IARJSET.2018.597.pdf\n\n- Convolutional Neural Networks for Toxic Comment Classification\nhttps://arxiv.org/pdf/1802.09957.pdf\n\n- A Machine Learning Approach to Comment Toxicity Classification\nhttps://arxiv.org/ftp/arxiv/papers/1903/1903.06765.pdf\n\n- Adversarial Text Generation for Google’s Perspective \nhttps://www.nyit.edu/files/engineering/SOECS_REU2018_PosterPresentation_AdversarialTextGenerationForGooglePerspective.pdf\n\n- Content Moderation Across Multiple Platforms with Capsule Networks and Co-Training\nhttp://precog.iiitd.edu.in/Publications_files/Vani_Agarwal_Masters_Thesis.pdf",
    "813641": "Thanks!",
    "814724": "Great ,Thanks for sharing!",
    "815010": "Thanks 🤜🏼",
    "1991976": "Thanks a lot."
  },
  "source": "meta"
}