Fact-checking for bloggers: how to quickly check information before publishing

Nowadays, it only takes one post or video on social media for false information to spread faster. One of the main drivers of this process are bloggers with a wide audience and significant influence. That’s why it’s so important to verify any information you want to share online. In this article, we explain why fact-checking is especially important for influencers, and what happens when it’s ignored.

Why does information from bloggers spread faster?

Social media algorithms, especially on short-form video platforms, facilitate the viral spread of content, including false ones. The pursuit of trends encourages bloggers to quickly jump into discussions without having time to verify the information, which greatly increases its reach.

Added to this is the effect of authority. Audiences tend to trust the opinions of popular authors, even if they aren’t experts on the topic. This cognitive bias makes disinformation spread by bloggers particularly persuasive and dangerous. 

Moreover, in the context of targeted disinformation campaigns, bloggers often become the target audience for manipulators. All it takes is convincing a few influential people of the “truth” of a fake, and it instantly reaches millions.

The consequences can be serious: from the loss of subscribers’ trust to legal liability for defamation or inciting ethnic or religious hatred. The dissemination of false information in the areas of health, science, or public safety can perpetuate dangerous myths, radicalize audiences, and even provoke illegal actions, placing bloggers under particular ethical and social responsibility.

AI, bots, and other threats

Bloggers are able to deliver content to millions quickly. And this force is reinforced by new threats: generative AI, bots, anonymous stuffing.

Despite the stated ethical limitations, neural network security systems can be circumvented: there are jailbreak methods on the Network that allow the generation of prohibited content. It, in turn, is used to illustrate disinformation, giving it the appearance of credibility.

For example, journalists at The New York Times demonstrated that some new neural network models can generate disinformation—they were able to create content featuring children and long-dead public figures (Martin Luther King and Michael Jackson), scenes of violence, rigged elections, and the arrest of migrants—all without their consent and bypassing built-in filters. However, the neural network was unable to generate similar content featuring modern public figures.

«Sora, which is currently accessible only by invitation from an existing user, doesn’t require account verification. This means users can sign up under a false name and profile picture. (To create an AI double, users must upload a video of themselves to the app. In testing conducted by The Times, Sora rejected attempts to create AI doubles based on videos of famous people.) The app will generate content featuring children without issue, as well as content featuring long-dead public figures such as the Rev. Dr. Martin Luther King Jr. and Michael Jackson.

The app couldn’t create videos featuring President Trump or other world leaders. But when Sora was asked to create a video of a political rally, in which participants wore blue and held signs proclaiming rights and freedoms, it produced a video with the unmistakable voice of former President Barack Obama».

“Although the app refused to create violent images, it willingly showed store robberies and home break-ins captured by doorbell cameras. Sora developer posted a video from the app showing Sam Altman, CEO of Open AI, stealing from the Target store. It also created videos of bombs exploding on city streets and other fake images of war — content that is considered highly undesirable because of its ability to mislead the public about global conflicts.”

Real-world consequences of such inaccurate generative content are already occurring: for example, in England, train service was temporarily suspended due to a generated image of a collapsed bridge after a real earthquake, even though the bridge was actually undamaged. This prank caused transport disruptions and unnecessary inspection costs.

«The trains were stopped after an artificial intelligence-generated photo appeared on social media after the earthquake, showing serious damage to the bridge. The tremor, which occurred on Wednesday evening, was felt throughout Lancashire and the southern part of the Lake District. Network Rail said it had been notified of an image that appeared to show severe damage to the Carlisle Bridge in Lancaster at 00:30 GMT and had halted rail service across the bridge while safety checks were carried out».

In addition to AI content, bots—fake accounts that can stir up conflict in comments, serve as sources of false news, and suggest hot topics for bloggers to cover—pose a threat.

Many of these accounts are completely controlled by AI and publish unverified content that is not labeled as generative by platforms, which is why misinformation spreads uncontrollably.

At the same time, bloggers themselves actively use AI not only to create media, but also to write scripts, analyze comments, and plan content. It should be understood here that neural networks are trained on open data, which is not always reliable, and ambiguous queries often lead to errors and distortions.

How to check the information before publishing it?

To check the information before publication, it is worth considering the basic principles of fact-checking, which always remain relevant:

1. Search for the original source;

2. Clarifying the context;

3. Assessment of the author’s expertise;

4. Conducting a cross-check based on independent sources.

It will be useful to remember what fakes are, how to verify and methods of countering
false information.

But specific practices are also critically important for bloggers:

• Checking each offer, especially if it was sent by subscribers or “sources”. Search for the purpose of the information guide.
• Skepticism about viral information. The most emotional and “hot” topics are most often fake, but they get the maximum coverage.
• Distrust of the “authority” of other bloggers. Even large channels can make mistakes or spread misinformation.
• Analyzing your content for distortion: clickbait and provocative framing can distort the meaning beyond recognition, misleading the audience.
• Risk assessment of AI-generated content. Even “harmless” videos (for example, about animal attacks) can increase social tension in vulnerable regions.
• Avoiding doxing — the deliberate collection and publication of personal information about a person without their consent. Subscribers often send materials with personal information. Before publishing, you should make sure that all confidential information is deleted, otherwise you can cause harassment and de-anonymization (deprivation of anonymity).
• Awareness of cognitive biases: confirmation bias, survivor error, overgeneralization. The development of critical and analytical thinking is the foundation of responsible content—making.

Ignoring these principles can turn a blogger into a distributor of not just inaccuracies, but also dangerous misinformation — from conspiracy theories to false health recommendations.

A vivid example is the fakes about COVID-19, the consequences of which are still felt in the public consciousness.

As opinion leaders, they must approach content creation with special responsibility. Techniques that increase engagement should not become tools of deception. After all, influence without responsibility is a path to loss of trust and real harm.