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From Algolit

 
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|Number of words: || 1.039.789
 
|Number of words: || 1.039.789
 
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|Unique words: || 6.4136
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|Unique words: || 64.136
 
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| Source: || English Wikipedia
 
| Source: || English Wikipedia
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The [https://figshare.com/projects/Wikipedia_Talk/16731 original dataset] consists of:
 
The [https://figshare.com/projects/Wikipedia_Talk/16731 original dataset] consists of:
*A corpus of all 95 million user and article talk diffs made between 2001–2015 scored by the personal attack model.
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*A corpus of all 95 million user and article talk diffs made between 2001 and 2015 scored by the personal attack model.
 
*A human annotated dataset of 1m crowd-sourced annotations that cover 100k talk page diffs (with 10 judgements per diff).
 
*A human annotated dataset of 1m crowd-sourced annotations that cover 100k talk page diffs (with 10 judgements per diff).
  

Latest revision as of 13:55, 2 November 2017

Type: Dataset
Number of words: 1.039.789
Unique words: 64.136
Source: English Wikipedia
Developed by: Wikimedia Foundation

The Detox dataset is a project by Wikimedia and Perspective API to train a neural network that would detect the level of toxicity of a comment.

The original dataset consists of:

  • A corpus of all 95 million user and article talk diffs made between 2001 and 2015 scored by the personal attack model.
  • A human annotated dataset of 1m crowd-sourced annotations that cover 100k talk page diffs (with 10 judgements per diff).

For Algolit, a smaller section of the Detox dataset was used, taken from Jigsaw's Github, which contains both constructive and vandalist edits.