A Glossary of Misinformation Terms
Last updated June 2026
Bad information often works because we do not have a name for what is being done to us. Once you can label a tactic — "that is cherry-picking", "that is a strawman" — it loses a lot of its power. This glossary collects the terms that come up most often when people talk about misleading news, with a plain definition and a short, generic example for each.
You do not need to memorise the whole list. Skim it once, and the next time a headline feels slippery you will have the vocabulary to say exactly why. We have grouped the terms loosely — the different kinds of false information, the rhetorical tricks used to push it, and the ways it spreads — but the lines between these groups are blurry in practice.
Types of false information
Misinformation
False or misleading information shared without the intent to deceive. The person passing it on usually believes it is true. Example: someone reshares an old photo of a flood thinking it shows a storm that happened yesterday. They are wrong, but they are not lying.
Disinformation
False or misleading information created or spread deliberately to deceive, profit, or cause harm. The distinction from misinformation is intent. Example: a coordinated account network invents a fake quote and pushes it to damage a public figure's reputation.
Malinformation
Information that is genuinely true but is shared out of context, or made public specifically to mislead or hurt. Example: a real private document is leaked and stripped of the context that explains it, so the accurate facts create a false overall impression.
Deepfake
Synthetic audio, video, or images generated by AI to convincingly show a real person saying or doing something they never did. Example: a video clip in which a well-known voice appears to endorse a product, produced entirely by a voice-cloning tool.
Cheapfake
A misleading clip made with simple, low-tech edits rather than AI — slowing footage down, speeding it up, cropping out context, or relabelling old video as new. Cheapfakes are far more common than deepfakes because they take seconds to make. Example: a speech clipped to remove the sentence that changes its meaning.
Clickbait
Headlines or thumbnails engineered to maximise curiosity and clicks, often by overstating, withholding, or distorting what the article actually says. The story rarely delivers what the headline promised. Example: "You won't believe what this council decided" attached to a routine planning notice.
Rhetorical tricks
Cherry-picking
Selecting only the data points or examples that support a claim while ignoring the larger body of evidence that contradicts it. Example: quoting the one cold month in a record-warm year to argue a trend is not real.
Strawman
Misrepresenting someone's argument as a weaker or more extreme version, then defeating that distorted version instead of what they actually said. Example: "They want to ban all cars" in response to someone proposing a low-traffic zone on one street.
False balance
Presenting two sides as equally credible when the evidence overwhelmingly favours one, usually in the name of "fairness". It leaves audiences thinking a settled question is still wide open. Example: giving a lone dissenter equal airtime against a broad scientific consensus, as though it were a 50-50 debate.
False equivalence
Treating two things as comparable when they differ in scale, evidence, or seriousness. Closely related to false balance, but broader. Example: equating a single anecdotal complaint with the findings of a large systematic review, as if they carry the same weight.
Gish gallop
Overwhelming an opponent or audience with a rapid flood of claims — too many to fact-check in real time — so that some will go unchallenged and seem to stand. Quantity substitutes for quality. Example: a post that lists twenty dubious "facts" in one breath, daring you to refute each.
Whataboutism
Deflecting a criticism by pointing to someone else's alleged wrongdoing rather than addressing the point at hand. It changes the subject while looking like a rebuttal. Example: answering "this policy failed" with "well, what about the other side's policy?"
Anecdotal evidence
A single personal story or example used as if it proves a general pattern. Stories are vivid and persuasive, but one case tells you little about how common something is. Example: "My neighbour took it and felt great, so it works" — which says nothing about the average effect.
Appeal to authority
Treating a claim as true simply because an authority figure said it, especially when that person is speaking outside their field or when the wider evidence is being ignored. Genuine expertise matters; a title alone does not settle a question. Example: citing a celebrity's view on a medical matter as if it were clinical evidence.
Correlation vs causation
Assuming that because two things happen together, one must cause the other. Many correlations are coincidence or are explained by a third factor. Example: ice-cream sales and drowning rates both rise in summer, but ice cream does not cause drowning — hot weather drives both.
Sealioning
Persistently demanding evidence and debate in a tone of polite reasonableness, while actually trying to exhaust and harass rather than understand. It weaponises the appearance of good faith. Example: endlessly replying "I'm just asking questions, can you prove it?" long after a point has been answered.
How it spreads
Astroturfing
Manufacturing the appearance of grassroots support — through fake accounts, paid posters, or coordinated campaigns — so a fringe view looks popular and organic. The name plays on "grassroots" being faked with artificial turf. Example: hundreds of near-identical comments praising a product, all posted within minutes.
Confirmation bias
Our tendency to notice, believe, and remember information that fits what we already think, while discounting what does not. It is not a trick others play on us so much as a built-in shortcut that misinformation exploits. Example: accepting a flattering claim about your own side instantly, but demanding proof for the same kind of claim about the other.
Echo chamber
A social setting — often online — where you mostly encounter views that match your own, because the people and groups around you share them. Disagreement is rare, so weak claims go unchallenged. Example: a group where every member already agrees, so a false rumour spreads unchecked.
Filter bubble
A narrowing of what you see caused by personalisation algorithms, which feed you more of what you already engage with. Similar to an echo chamber, but driven by software rather than your own choice of company. Example: a feed that quietly stops showing you anything that challenges your existing views.
Illusory truth effect
The well-documented tendency to believe a statement more the more often we hear it, regardless of whether it is true. Repetition feels like familiarity, and familiarity feels like truth. Example: a slogan repeated so often that it starts to sound obviously correct, even with no evidence behind it.
Prebunking and debunking
Two responses to false information. Debunking corrects a falsehood after it has spread. Prebunking warns people about a misleading tactic before they meet it, so they recognise and resist it — rather like a mental vaccine. Example: explaining how a common scam works so readers spot it when it lands in their inbox.
Most of these tactics leave fingerprints in the text itself — a strawman, a cherry-picked figure, a headline that oversells. Fact or Fiction News reads an article and flags exactly this kind of move, claim by claim, so you can see where the reasoning bends.
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