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README.md
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A large part of these data sources are open-sources academic datasets, and the labels for Y domains were also collected manually
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from online sources (governmental, journalistic or academic) that gathered domain lists in non-machine readable format.
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Some of the primary contributors to the dataset are:
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- [UT1](http://dsi.ut-capitole.fr/blacklists/index_en.php) by the University of Toulouse Capitole (88.6%),
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- [DQR](https://academic.oup.com/pnasnexus/article/2/9/pgad286/7258994?login=false) by Lin et al. (7.6%),
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- Wikipedia (3.6%),
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- [Lasser et al.]()'s data (3.1%).
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The full composition is provided below for both dataset versions.
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#### Reliability
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#### Factuality
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pool.csv: 5671880
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downsampled.csv: 149086
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Reliability continuous
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value domains
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low 6440
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high 5426
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medium 309
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Reliability categories
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----------------------
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A large part of these data sources are open-sources academic datasets, and the labels for Y domains were also collected manually
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from online sources (governmental, journalistic or academic) that gathered domain lists in non-machine readable format.
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The full composition is provided below for both dataset versions, the downsampled one and the full variant:
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- `domain-pool`: 5,671,880 domains, labelled across three axes, all with at least one categorical label that can pertain to its reliability (e.g., 'fake news' or 'adult content').
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Categories are listed below.
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- `domain-pool-downsampled`: 149,086 domains, where the dominating categories (ones with more than 20,000 datapoints) are downsampled to 15,000 or less.
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Due to overlaps between datasets, this brings some of the dominating categories to counts between 10 and 15,000; the processing includes an iterative optimizer that tries to minimize such loss.
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This is beneficial because the entire domain pool is predominantly composed of a few large categories (e.g., adult content accounts for more than 4 million domains).
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Some of the primary contributors to the dataset are:
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- [UT1](http://dsi.ut-capitole.fr/blacklists/index_en.php) by the University of Toulouse Capitole (88.6%),
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- [DQR](https://academic.oup.com/pnasnexus/article/2/9/pgad286/7258994?login=false) by Lin et al. (7.6%),
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- Wikipedia (3.6%),
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- [Lasser et al.]()'s data (3.1%).
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#### Reliability
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Reliability as a broad category encompasses three types of labels; two quantitative, and one qualitative:
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1. **Continuous score ( n = 11,980 ):** these are academic-sourced float on [0.0,1.0] that explicitly relates to the domain's reliability as assessed by expert fact-checkers.
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2. **3-class ( n = 12,053 ):** same type of source and meaning, these span three levels: [low, medium, high].
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3. **Categorical ( n = 149,086 ):** these are broader categories that describe the nature of the website. Most are directly related to the website's reliability (e.g. 'malware'), while some are more neutral (e.g. 'sports').
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More precisely,
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##### Reliability (continuous)
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- Count: 11,980
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<!-- - Min score: 0.00, -->
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<!-- - 25th perc.: 0.44, -->
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<!-- - median: 0.64, -->
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- mean: 0.59,
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<!-- - 75th perc. = 0.75,
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- max = 1.00 -->
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Distribution:
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| Range | [0.0, 0.1) | [0.1, 0.2) | [0.2, 0.3) | [0.3, 0.4) | [0.4, 0.5) | [0.5, 0.6) | [0.6, 0.7) | [0.7, 0.8) | [0.8, 0.9) | [0.9, 1.0] |
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|--------------|------------|------------|------------|------------|------------|------------|------------|------------|------------|------------|
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| Domains | 49 | 161 | 809 | 1252 | 1751 | 1133 | 2415 | 2969 | 1356 | 84 |
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##### Reliability 3-class
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| Value | Domains |
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|--------|---------|
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| low | 6440 |
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| high | 5426 |
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| medium | 309 |
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#### Factuality
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<!-- pool.csv: 5671880
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downsampled.csv: 149086
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Reliability continuous
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value domains
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low 6440
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high 5426
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medium 309 -->
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Reliability categories
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----------------------
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