Social media has become one of the main ways people receive news, learn about current events, and communicate with others. However, the same platforms that make information easily accessible can also make misinformation easier to spread. False or misleading information can reach thousands or even millions of people before users have time to determine whether what they are seeing is actually true. Two platforms where I regularly see information being shared are TikTok and Instagram. Both platforms have developed policies and tools intended to address misinformation, but their approaches also have limitations. Looking at these platforms is especially interesting because they rely heavily on visual content, recommendations, algorithms, and user engagement.
TikTok’s Approach to Misinformation
TikTok addresses misinformation through its Community Guidelines, particularly its rules involving integrity and authenticity. TikTok states that it does not allow misinformation that could cause significant harm to individuals or society. Depending on the type of content involved, TikTok may remove a post, make it ineligible for recommendation in the For You feed, add warning or informational labels, or provide users with additional context.
This is important because TikTok’s For You Page can introduce users to information from people they do not personally follow. A person does not have to search for a claim to encounter it. The recommendation system can place a video directly in front of them based on their interests and previous activity. Because of this, reducing the recommendation of questionable information may sometimes be just as important as removing content.
TikTok has also developed policies addressing manipulated and artificial intelligence-generated media. Its AI-generated content policies require certain realistic AI-generated content to be labeled. This has become increasingly important because generative AI makes it possible to produce convincing images, audio, and videos that may cause viewers to believe something happened when it did not.
One example of TikTok’s approach can occur when a questionable video begins circulating about an important public issue. If the content violates TikTok’s harmful misinformation rules, it can be removed. In other circumstances, content may remain available but become ineligible for recommendation. TikTok has also used prompts and labels to encourage users to reconsider sharing information that has not been verified.
I think this approach has merit because misinformation is not always a simple true-or-false issue. Removing clearly harmful false information is important, but limiting recommendations can also reduce how quickly questionable information spreads while it is being evaluated. Research published in Science Advances found that shifting people’s attention toward accuracy can improve the quality of news they subsequently share online (Pennycook et al., 2021).
From my own experience using TikTok, however, misinformation can still be difficult to recognize. Videos are short, entertaining, and often designed to immediately grab someone’s attention. A creator can speak confidently, use text on the screen, or reference a supposed study without actually providing enough information for viewers to verify the claim. I have also noticed how easy it is to continue scrolling without leaving the app to research what someone has said. This connects with what I have learned about lateral reading and the SIFT method: instead of immediately trusting a post, users should stop, investigate the source, find better coverage, and trace claims back to their original context.
Instagram’s Approach to Misinformation
Instagram, which is owned by Meta, also uses policies and enforcement systems to address misinformation. Meta provides information about these efforts through its Transparency Center. Meta’s approach has changed over time, making it especially important to look at current policies rather than assuming that systems used several years ago are still operating in exactly the same way.
Instagram also addresses manipulated and AI-generated media. Meta has introduced labeling and disclosure systems intended to give users more information when content has been created or significantly altered using artificial intelligence. Meta explains its approach to AI content through its Transparency Center. These labels are important because an image or video can look realistic even when the event being shown never occurred.
Instagram’s recommendation systems are another important part of the misinformation issue. Information does not only spread because someone intentionally searches for it. Content can appear through Explore, Reels, suggested posts, and shares from other users. Meta therefore has rules determining what content is eligible to be recommended. Its Recommendation Guidelines explain that some content may be allowed on the platform while still being excluded from recommendation surfaces.
I think reducing distribution can be useful because deleting every questionable post is unrealistic. There is also a difference between information that is completely false, information that lacks context, personal opinions, satire, and information that is still developing. Recommendation restrictions allow platforms to reduce amplification without treating every questionable claim exactly the same.
At the same time, Instagram has similar weaknesses to TikTok. A misleading Reel or infographic can still receive significant engagement through likes, comments, saves, and shares. Users may also see information reposted by someone they know and trust, which can make the claim appear more believable. This demonstrates why platform policies alone cannot completely solve misinformation.
What Could TikTok and Instagram Do Better?
One improvement I would recommend for both platforms is making context more visible before users interact with questionable information. Instead of placing important context where users can easily ignore it, platforms could provide clearer prompts before someone reposts or shares content that has been identified as disputed, manipulated, or lacking reliable evidence. These prompts could encourage users to review the original source before continuing.
Both platforms could also make source information easier to access. For example, when creators discuss scientific or health research, platforms could encourage direct links to the original research rather than allowing screenshots or vague references to serve as evidence. Users should not have to search through dozens of comments trying to figure out where a statistic originated.
Another improvement would be greater transparency about recommendation systems. Platforms should regularly explain how misinformation enforcement affects recommendation and provide researchers with enough information to evaluate whether those systems actually reduce exposure. A policy can sound effective on paper, but the more important question is whether it works once millions of users begin interacting with content.
Finally, media literacy should become a larger part of the solution. TikTok and Instagram cannot investigate every misleading statement before someone sees it. Platforms could integrate short educational reminders teaching users strategies such as lateral reading, checking original sources, and searching for independent coverage. Research has also found evidence that short “prebunking” videos can improve people’s ability to recognize common manipulation techniques used in misinformation (Roozenbeek et al., 2022).
Conclusion
TikTok and Instagram have both developed tools to address misinformation, including content rules, recommendation restrictions, contextual information, and policies surrounding manipulated or AI-generated media. These efforts can reduce the reach of some misleading content, but they cannot completely prevent misinformation from spreading. In my experience, one of the biggest challenges is how quickly users consume and share information. Social media encourages immediate reactions, while determining whether something is accurate often requires slowing down and investigating.
For that reason, I believe the strongest approach combines platform responsibility with better media literacy. TikTok and Instagram should continue improving enforcement and transparency, but users also need accessible tools that encourage them to question information before believing or sharing it. Misinformation will probably never disappear completely from social media, but platforms can make it more difficult for misleading information to spread unchecked while giving users better tools to recognize it.
References
Meta. (n.d.). Approach to labeling AI-generated content and manipulated media. Meta Transparency Center. https://transparency.meta.com/features/approach-to-labeling-ai-generated-content/
Meta. (n.d.). Recommendation guidelines. Meta Transparency Center. https://transparency.meta.com/policies/recommendations/
Meta. (n.d.). Transparency Center. https://transparency.meta.com/
Pennycook, G., Epstein, Z., Mosleh, M., Arechar, A. A., Eckles, D., & Rand, D. G. (2021). Shifting attention to accuracy can reduce misinformation online. Nature, 592, 590–595. https://doi.org/10.1038/s41586-021-03344-2
Roozenbeek, J., van der Linden, S., Goldberg, B., Rathje, S., & Lewandowsky, S. (2022). Psychological inoculation improves resilience against misinformation on social media. Science Advances, 8(34), eabo6254. https://doi.org/10.1126/sciadv.abo6254
TikTok. (n.d.). AI-generated content. TikTok Support. https://support.tiktok.com/en/using-tiktok/creating-videos/ai-generated-content
TikTok. (n.d.). Integrity and authenticity. Community Guidelines. https://www.tiktok.com/community-guidelines/en/integrity-authenticity/
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