The Case for Claim Difficulty Assessment in Automatic Fact Checking
Not on the map. Why?
Abstract (arXiv)
Fact-checking is the process of evaluating the veracity of claims (i.e., purported facts). In this opinion piece, we raise an issue that has received little attention in prior work -- that some claims are far more difficult to fact-check than others. We discuss the implications this has for both practical fact-checking and research on automated fact-checking, including task formulation and dataset design. We report a manual analysis undertaken to explore factors underlying varying claim difficulty and identify several distinct types of difficulty. We motivate this new claim difficulty prediction task as beneficial to both automated fact-checking and practical fact-checking organizations.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 20 of its 37 references that are in the map. First posted on arXiv 20 Sep 2021.
Builds on
20 of 37 references.
References · 20
- 2017On Calibration of Modern Neural Networkscited by 4,860
- 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,362
- 2021Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategiescited by 736
- 2020Fact or Fiction: Verifying Scientific Claimscited by 546
- 2019TabFact: A Large-scale Dataset for Table-based Fact Verificationcited by 425
- 2017"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detectioncited by 361
- 2020HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verificationcited by 199
- 2019MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claimscited by 169
- 2020Generating Fact Checking Explanationscited by 132
- 2021Decontextualization: Making Sentences Stand-Alonecited by 101
- 2018DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learningcited by 100
- 2021COVID-Fact: Fact Extraction and Verification of Real-World Claims on COVID-19 Pandemiccited by 100
8 more
- 2021X-FACT: A New Benchmark Dataset for Multilingual Fact Checkingcited by 90
- 2019A Richly Annotated Corpus for Different Tasks in Automated Fact-Checkingcited by 74
- 2018Integrating Stance Detection and Fact Checking in a Unified Corpuscited by 41
- 2018Confidence Modeling for Neural Semantic Parsingcited by 33
- 2020A Review of Winograd Schema Challenge Datasets and Approachescited by 27
- 2020CheckThat! at CLEF 2020: Enabling the Automatic Identification and Verification of Claims in Social Mediacited by 25
- 2020Joint Verification and Reranking for Open Fact Checking Over Tablescited by 16
- 2019Long-length Legal Document Classificationcited by 10
Built on by
Citing papers per year: 2022: 1; 2023: 3; 2024: 1.
5 papers.
- 2023AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Webcited by 144
- 2023Complex Claim Verification with Evidence Retrieved in the Wildcited by 110
- 2022Generating Literal and Implied Subquestions to Fact-check Complex Claimscited by 66
- 2023Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AIcited by 9
- 2024Contrastive Learning to Improve Retrieval for Real-world Fact Checkingcited by 6
- 2024Contrastive Learning to Improve Retrieval for Real-world Fact Checking7 Oct 2024
- 2023Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AI14 Aug 2023
- 2023AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web22 May 2023
- 2023Complex Claim Verification with Evidence Retrieved in the Wild19 May 2023
- 2022Generating Literal and Implied Subquestions to Fact-check Complex Claims14 May 2022