Quantitative Claim and Citation Verification Dataset for Social Media Advertising

#numerical claim verification #citation evidence validation #metric consistency checking #social media advertising compliance #quantitative advertising claim verification #citation accuracy assessment
  • 5000
  • 0.3GB
  • JSON
  • CATL
  • MOBIUSI INCMOBIUSI INC
Updated:2026-10-19

AI Analysis & Value Prop

This dataset contains synthetic quantitative claims for social media ads, including percentages, statistics, averages, sample sizes, and survey results, paired with citation excerpts that may support or contradict each claim. The excerpts provide verification details such as units, denominators, time ranges, and calculation methods, enabling checks of numerical evidence, metric definitions, and applicable conditions. It is designed for training and evaluating ad content review, fact-checking, and citation verification systems.

Dataset Insights

Sample Examples

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Technical Specifications

FieldTypeDescription
file_namestringFile name
claim_textstringThe original synthetic quantitative claim from a social media advertisement that requires verification.
citation_textstringThe original excerpt used to support or contradict the ad claim, including verifiable details such as units, denominators, time ranges, or calculation methods.
claim_analysisobjectThe quantitative metrics and applicable conditions extracted from the original ad claim.
citation_analysisobjectThe numerical evidence, metric definitions, and applicable conditions extracted from the citation excerpt.
validation_resultobjectThe item-level support judgments and overall conclusion produced by comparing the ad claim with the citation excerpt.

Compliance Statement

Authorization TypeProprietary - Commercial AI Training License (No Redistribution)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset contain?
It contains synthetic quantitative claims for social media ads paired with citation excerpts. Claim types include percentages, statistics, averages, sample sizes, and survey results. Excerpts include details such as units, denominators, time ranges, or calculation methods to help determine whether they support or contradict a claim.
What record structure and verification details are provided?
Each record includes the original claim, citation excerpt, claim analysis, citation analysis, and validation result. The validation result provides item-level support judgments and an overall conclusion, making the data suitable for checking numerical evidence, metric definitions, and applicable conditions. Confirm the product page or delivery notes for the exact dataset size and format.
How can I access the dataset?
Check the current product page for available access methods, delivery formats, and related instructions. Contact the data provider before purchase or application if you need file specifications or processing details that are not listed.
Is the dataset suitable for production ad review, and what licensing applies?
The dataset is intended primarily for training and evaluating citation verification, numerical fact-checking, and ad content review capabilities. Because its content is synthetic, it should not be treated as real advertising performance or real survey results. Check the product page or a separate license agreement for commercial use, redistribution, and other usage rights.

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Cite this Work

@dataset{Mobiusi2026,
  title={Quantitative Claim and Citation Verification Dataset for Social Media Advertising},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/5434acd860b79e8abf99237675df41e8?dataset_scene_cate_type=9},
  urldate={2026-10-14},
  keywords={social media advertising dataset,quantitative claim verification,citation verification data,advertising fact checking,marketing content review,numerical evidence matching,synthetic text dataset,knowledge grounding},
  version={1.0}
}

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