# ClaimRank: Detecting Check-Worthy Claims in Arabic and English

arXiv: https://arxiv.org/abs/1804.07587 · HTML: https://mlsanity.com/paper/1804.07587/

## Key facts

- Cited by 27 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Apr 2018.

## Built on by (most cited first, 27 of 27)

- [Automated Fact-Checking for Assisting Human Fact-Checkers](https://mlsanity.com/paper/2103.07769/) (2021)
- [Automated Fact-Checking: A Survey](https://mlsanity.com/paper/2109.11427/) (2021)
- [Claim Detection for Automated Fact-checking: A Survey on Monolingual, Multilingual and Cross-Lingual Research](https://mlsanity.com/paper/2401.11969/) (2024)
- [NewsClaims: A New Benchmark for Claim Detection from News with Attribute Knowledge](https://mlsanity.com/paper/2112.08544/) (2021)
- [Empowering the Fact-checkers! Automatic Identification of Claim Spans on Twitter](https://mlsanity.com/paper/2210.04710/) (2022)
- [Overview of the CLEF-2019 CheckThat!: Automatic Identification and Verification of Claims](https://mlsanity.com/paper/2109.15118/) (2021)
- [Human-in-the-loop Evaluation for Early Misinformation Detection: A Case Study of COVID-19 Treatments](https://mlsanity.com/paper/2212.09683/) (2022)
- [SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checking](https://mlsanity.com/paper/2110.13090/) (2021)
- [Entity-based Claim Representation Improves Fact-Checking of Medical Content in Tweets](https://mlsanity.com/paper/2209.07834/) (2022)
- [A Second Pandemic? Analysis of Fake News About COVID-19 Vaccines in Qatar](https://mlsanity.com/paper/2109.11372/) (2021)
- [Searching for Structure in Unfalsifiable Claims](https://mlsanity.com/paper/2209.00495/) (2022)
- [Multilingual Detection of Check-Worthy Claims using World Languages and Adapter Fusion](https://mlsanity.com/paper/2301.05494/) (2023)
- [Overview of the CLAIMSCAN-2023: Uncovering Truth in Social Media through Claim Detection and Identification of Claim Spans](https://mlsanity.com/paper/2310.19267/) (2023)
- [Self-Supervised Claim Identification for Automated Fact Checking](https://mlsanity.com/paper/2102.02335/) (2021)
- [Diverse, but Divisive: LLMs Can Exaggerate Gender Differences in Opinion Related to Harms of Misinformation](https://mlsanity.com/paper/2401.16558/) (2024)
- [Check-worthy Claim Detection across Topics for Automated Fact-checking](https://mlsanity.com/paper/2212.08514/) (2022)
- [Leveraging Social Discourse to Measure Check-worthiness of Claims for Fact-checking](https://mlsanity.com/paper/2309.09274/) (2023)
- [Assessing Effectiveness of Using Internal Signals for Check-Worthy Claim Identification in Unlabeled Data for Automated Fact-Checking](https://mlsanity.com/paper/2111.01706/) (2021)
- [Z-Index at CheckThat! Lab 2022: Check-Worthiness Identification on Tweet Text](https://mlsanity.com/paper/2207.07308/) (2022)
- [RAVE: Retrieval and Scoring Aware Verifiable Claim Detection](https://mlsanity.com/paper/2509.15793/) (2025)
- [Entity-Assisted Language Models for Identifying Check-worthy Sentences](https://mlsanity.com/paper/2211.10678/) (2022)
- [MythQA: Query-Based Large-Scale Check-Worthy Claim Detection through Multi-Answer Open-Domain Question Answering](https://mlsanity.com/paper/2307.11848/) (2023)
- [HYBRINFOX at CheckThat! 2024 -- Task 1: Enhancing Language Models with Structured Information for Check-Worthiness Estimation](https://mlsanity.com/paper/2407.03850/) (2024)
- [ContextClaim: A Context-Driven Paradigm for Verifiable Claim Detection](https://mlsanity.com/paper/2603.30025/) (2026)
- [Trust but Verify: Introducing DAVinCI -- A Framework for Dual Attribution and Verification in Claim Inference for Language Models](https://mlsanity.com/paper/2604.21193/) (2026)
- [Calibrating Small Language Models for Claim Check-Worthiness Detection](https://mlsanity.com/paper/2608.30731/) (2026)
- [VEX-Bench: Benchmarking Verification Complexity of LLM-Generated Misinformation](https://mlsanity.com/paper/2609.35028/) (2026)

## Abstract (arXiv)

We present ClaimRank, an online system for detecting check-worthy claims. While originally trained on political debates, the system can work for any kind of text, e.g., interviews or regular news articles. Its aim is to facilitate manual fact-checking efforts by prioritizing the claims that fact-checkers should consider first. ClaimRank supports both Arabic and English, it is trained on actual annotations from nine reputable fact-checking organizations (PolitiFact, FactCheck, ABC, CNN, NPR, NYT, Chicago Tribune, The Guardian, and Washington Post), and thus it can mimic the claim selection strategies for each and any of them, as well as for the union of them all.