Our Labels & Standards

Note: The following documentation is subject to occasional reviews and revisions.

Headline format

Label: Fact-checking conclusion

Labels

False

The claim/statement is demonstrably false. The photo/video has been doctored. Stories prove that the information is not substantiated with facts or totally made up.  Stories investigate the factual validity of the claim and/or the authenticity of the photo/video.

Misleading

 The claim is accompanied by non-altered evidence, but it is used out of context or in a demonstrably misleading way. The key evidence may be fact-based, but the claim and information associated with the evidence are not true.

No evidence

The claim cannot be substantiated with evidence in any way. Used when the information is very likely made up, or a group of information does not constitute evidence logically in any fashion, often with unsubstantiated causal associations or cherry-picked partial facts).

Investigation

The story looks into a series of misinformation and/or its ecosystem on a specific topic. It tries to verify multiple claims and/or examines a larger narrative.

Analysis

There are two types of analysis. 1) Although the claim may be based on facts or unaltered visual material, the evidence indicates the overall narrative is false or misleading; 2) a series of fact-checks on the same or similar topics (when one label does not fit all investigations).

Explainer

The story tries to explain a complex background history and other relevant information surrounding persistent misinformation.

Verified

The claim has been independently verified. We have evidence to prove the claim is accurate.

Just in case

This label is used when a claim is clearly fiction, satire, opinion, or personal commentary (not a factual statement), but some users are observably mistaking it as fact. We also use this label to clarify statements and known facts when some people are demonstrably misunderstanding or misinterpreting them.

Guideline

• We strive to adhere to the globally recognized standards set by the International Fact-checking Network (IFCN) and its Code of Principles.
• We do not take any political position or advocate for any course of action.
• Every fact check by students is subject to editorial scrutiny by the faculty members at the School of Future Media at the University of Hong Kong.
• At the moment we do not use generative AI tools in our workflow, except for copyediting (checking style, grammar, and spelling). When specific AI tools are used in our investigation, we disclose the usage in the story.

Naming and contacting the source(s) of misinformation

• When misinformation comes from public figures or organizations, we reveal their names, images, and other information as shown on their websites and/or social media accounts.
• We will also reveal the sources when we can demonstrate they have produced and/or disseminated falsehood as part of political smear campaigns, scams, and other activities clearly intended to deceive others.
• We will anonymize real names, obscure the faces and leave out identifiable information when the sources do not seem ill-intentioned; however, we will still link to their original posts and writings even if they carry such information.
• Whenever possible, we will reach out to the original source(s) before we publish our fact-checking stories.

Correction policy

• When mistakes are made, we will correct the information in the original story with a clear indication of what has been changed. We will subsequently correct our relevant social media posts as well.

Verification methods and criteria

• To determine whether a claim is true or false, we gather first-hand information and supporting evidence.
• All evidence collected through our verification process is included in each story, using links, embedded materials, screen captures, or other appropriate formats.
• Each story is presented in a way that allows readers to replicate our verification process and reach their own conclusions.
• We select potentially problematic claims based on their likelihood of causing harm if untrue. This is our primary criterion when deciding what to fact-check.
• We also assess the significance of misinformation by evaluating its reach, such as the number of shares, comments, likes, and views.
• We do not publish any story unless we are fully confident in our conclusion.