April
#6
by
ekmpa
- opened
- README.md +8 -6
- april2025/edges.csv.gz +2 -2
- april2025/vertices.csv.gz +2 -2
- may2025/edges.csv.gz +0 -3
- may2025/vertices.csv.gz +0 -3
- nov2024/edges.csv.gz +2 -2
- nov2024/vertices.csv.gz +2 -2
README.md
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<!-- Provide a quick summary of the dataset. -->
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CrediBench is a large-scale, temporal webgraph constituted of web data pulled from [Common Crawl](https://commoncrawl.org/overview).
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## Dataset Details
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| Month | V | E | Min. deg. | Mean deg. | Max. deg. | Leaves (deg. = 1) | Edge Density |
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| -- | -- | -- | -- | -- | -- | -- | -- |
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| October 2024 | 50,288,479 | 1,074,971,387 | 1 | 42.75 | 17,112,352 | 30,278 | 4.3e-07 |
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| November 2024 |
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| December 2024 | 45,030,252 | 1,014,523,551 | 1 | 45.06 | 14,719,077 | 28,857 | 5.0e-07 |
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| January 2025 | 45,626,949 | 1,060,163,646 | 1 | 46.471 | 15,398,279 | 23,130 | 5.0e-07 |
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| February 2025 | 49,639,664 | 1,167,748,533 | 1 | 47.05 | 17,078,954 | 24,430 | 4.7e-07 |
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| March 2025 | 50,162,733 | 1,212,826,396 | 1 | 48.36 | 16,691,193 | 22,629 | 4.8e-07 |
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| April 2025 |
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| May 2025 |
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<!-- | June 2025 | 9,974,275 | 152,449,542 | 1 | 30.57 | 3,381,364 | 25,447 | 1.5e06 | -->
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**Content Embedding:**
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Domain-level content embeddings are generated using multiple LLM-based embedding models with varying LLM-model sizes and embedding dimensions.
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<!-- Provide a quick summary of the dataset. -->
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CrediBench 1.1 is a large-scale, temporal webgraph constituted of web data pulled from [Common Crawl](https://commoncrawl.org/overview).
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A prior version of the paper is [available here](https://arxiv.org/abs/2509.23340) (NPGML workshop @ NeurIPS 2025), with the latest version still under review.
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CrediBench 1.0, presented in this prior work, constituted of a static webgraph with 1 month's data, while the current version contains 3 months of data (October to December 2024, surrounding the U.S Federal elections, a period of increased misinformation).
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We are actively constructing and uploading more monthly graphs as well.
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## Dataset Details
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| Month | V | E | Min. deg. | Mean deg. | Max. deg. | Leaves (deg. = 1) | Edge Density |
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| -- | -- | -- | -- | -- | -- | -- | -- |
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| October 2024 | 50,288,479 | 1,074,971,387 | 1 | 42.75 | 17,112,352 | 30,278 | 4.3e-07 |
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| November 2024 (to redo) | 27,567,417 | 555,905,375 | 1 | 40.33 | 9,019,038 | 30,553 | 7.3e-07 |
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| December 2024 | 45,030,252 | 1,014,523,551 | 1 | 45.06 | 14,719,077 | 28,857 | 5.0e-07 |
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| January 2025 | 45,626,949 | 1,060,163,646 | 1 | 46.471 | 15,398,279 | 23,130 | 5.0e-07 |
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| February 2025 | 49,639,664 | 1,167,748,533 | 1 | 47.05 | 17,078,954 | 24,430 | 4.7e-07 |
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| March 2025 | 50,162,733 | 1,212,826,396 | 1 | 48.36 | 16,691,193 | 22,629 | 4.8e-07 |
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| April 2025 (to redo) | 17,998,846 | 349,717,108 | 1 | 38.86 | 5,284,367 | 25,606 | 1.1e-06 |
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<!-- | May 2025 | 5,833,993 | 87,752,862 | 1 | 30.08 | 1,581,282 | 17,683 | 2.6e-06 | -->
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<!-- | June 2025 | 9,974,275 | 152,449,542 | 1 | 30.57 | 3,381,364 | 25,447 | 1.5e06 | -->
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**Content Embedding:**
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Domain-level content embeddings are generated using multiple LLM-based embedding models with varying LLM-model sizes and embedding dimensions.
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april2025/edges.csv.gz
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april2025/vertices.csv.gz
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may2025/edges.csv.gz
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may2025/vertices.csv.gz
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nov2024/edges.csv.gz
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nov2024/vertices.csv.gz
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