#FactCheck - AI-Generated Clip of Lion Carrying Woman Shared as Real Incident

Introduction 

The link between social media and misinformation is undeniable. Misinformation, particularly the kind that evokes emotion, spreads like wildfire on social media and has serious consequences, like undermining democratic processes, discrediting science, and promulgating hateful discourses which may incite physical violence. If left unchecked, misinformation propagated through social media has the potential to incite social disorder, as seen in countless ethnic clashes worldwide.  This is why social media platforms have been under growing pressure to combat misinformation and have been developing models such as fact-checking services and community notes to check its spread. This article explores the pros and cons of the models and evaluates their broader implications for online information integrity.

How the Models Work 

1. Third-Party Fact-Checking Model (formerly used by Meta) Meta initiated this program in 2016 after claims of extraterritorial election tampering through dis/misinformation on its platforms. It entered partnerships with third-party organizations like AFP and specialist sites like Lead Stories and PolitiFact, which are certified by the International Fact-Checking Network (IFCN) for meeting neutrality, independence, and editorial quality standards. These fact-checkers identify misleading claims that go viral on platforms and publish verified articles on their websites, providing correct information. They also submit this to Meta through an interface, which may link the fact-checked article to the social media post that contains factually incorrect claims. The post then gets flagged for false or misleading content, and a link to the article appears under the post for users to refer to. This content will be demoted in the platform algorithm, though not removed entirely unless it violates Community Standards. However, in January 2025, Meta announced it was scrapping this program and beginning to test X’s Community Notes Model in the USA, before rolling it out in the rest of the world. It alleges that the independent fact-checking model is riddled with personal biases, lacks transparency in decision-making, and has evolved into a censoring tool. 
2. Community Notes Model ( Used by X and being tested by Meta): This model relies on crowdsourced contributors who can sign up for the program, write contextual notes on posts and rate the notes made by other users on X. The platform uses a bridging algorithm to display those notes publicly, which receive cross-ideological consensus from voters across the political spectrum. It does this by boosting those notes that receive support despite the political leaning of the voters, which it measures through their engagements with previous notes. The benefit of this system is that it is less likely for biases to creep into the flagging mechanism. Further, the process is relatively more transparent than an independent fact-checking mechanism since all Community Notes contributions are publicly available for inspection, and the ranking algorithm can be accessed by anyone, allowing for external evaluation of the system by anyone. 

CyberPeace Insights

Meta’s uptake of a crowdsourced model signals social media’s shift toward decentralized content moderation, giving users more influence in what gets flagged and why. However, the model’s reliance on diverse agreements can be a time-consuming process. A study (by Wirtschafter & Majumder, 2023) shows that only about 12.5 per cent of all submitted notes are seen by the public, making most misleading content go unchecked. Further, many notes on divisive issues like politics and elections may not see the light of day since reaching a consensus on such topics is hard. This means that many misleading posts may not be publicly flagged at all, thereby hindering risk mitigation efforts. This casts aspersions on the model’s ability to check the virality of posts which can have adverse societal impacts, especially on vulnerable communities. On the other hand, the fact-checking model suffers from a lack of transparency, which has damaged user trust and led to allegations of bias. 

Since both models have their advantages and disadvantages, the future of misinformation control will require a hybrid approach. Data accuracy and polarization through social media are issues bigger than an exclusive tool or model can effectively handle. Thus, platforms can combine expert validation with crowdsourced input to allow for accuracy, transparency, and scalability. 

Conclusion 

Meta’s shift to a crowdsourced model of fact-checking is likely to have bigger implications on public discourse since social media platforms hold immense power in terms of how their policies affect politics, the economy, and societal relations at large.  This change comes against the background of sweeping cost-cutting in the tech industry, political changes in the USA and abroad, and increasing attempts to make Big Tech platforms more accountable in jurisdictions like the EU and Australia, which are known for their welfare-oriented policies. These co-occurring contestations are likely to inform the direction the development of misinformation-countering tactics will take.  Until then, the crowdsourcing model is still in development, and its efficacy is yet to be seen, especially regarding polarizing topics. 

References 

• https://www.cyberpeace.org/resources/blogs/new-youtube-notes-feature-to-help-users-add-context-to-videos
• https://en-gb.facebook.com/business/help/315131736305613?id=673052479947730
• http://techxplore.com/news/2025-01-meta-fact.html 
• https://about.fb.com/news/2025/01/meta-more-speech-fewer-mistakes/ 
• https://communitynotes.x.com/guide/en/about/introduction 
• https://blogs.lse.ac.uk/impactofsocialsciences/2025/01/14/do-community-notes-work/?utm_source=chatgpt.com 
• https://www.techpolicy.press/community-notes-and-its-narrow-understanding-of-disinformation/ 
• https://www.rstreet.org/commentary/metas-shift-to-community-notes-model-proves-that-we-can-fix-big-problems-without-big-government/ 
• https://tsjournal.org/index.php/jots/article/view/139/57 

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Executive Summary

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A video has gone viral on social media claiming to show a fighter pilot climbing out of his aircraft mid-flight to repair its engine before crawling back into the cockpit and resuming the mission. The footage shows the pilot closing a compartment on the aircraft's fuselage, making his way back to the cockpit, and the canopy shutting as the aircraft continues flying. According to a study by the CyberPeace Research Wing , the viral video is not authentic but AI-generated.

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Claim

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On August 1, an X user named "Sarah for Trump" shared the clip, claiming it showed an Iranian fighter pilot repairing his aircraft in mid-air. The post alleged that the video had been released by Iran's Revolutionary Guards to intimidate the United States and Israel. Text overlaid on the video read: "A brave maneuver by an Iranian pilot that no pilot in the world has ever performed." (At the time of publishing this story, the video had garnered 2.6 million views)

At the time this story was published, the video had received more than 2.6 million views.

https://x.com/SarahAllisonFl/status/2083589225912402201 

https://archive.ph/fkW32

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FactCheck

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To verify the claim, we first analysed the viral video using the InVid verification tool and extracted several keyframes. A reverse image search of these frames through Google Lens led us to multiple social media posts carrying the same video with similar claims. The search also led us to an Instagram account named "viralism.ai", where the identical video had been uploaded on June 14. A comparison confirmed that the visuals matched the viral clip exactly, indicating that the Instagram upload was the original source from which the video was later circulated with a false narrative.

https://www.instagram.com/reel/DZkIrEijc89/

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A review of the Instagram account further revealed that it primarily publishes AI-generated content. The account's description clearly states "AI Viral Videos and Trends," indicating that the video was created using artificial intelligence rather than depicting a real event. To further confirm our findings, we analysed the clip using the AI detection tool Hive Moderation. The results showed a high probability that the video was AI-generated, with several portions of the footage being flagged as synthetic

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Conclusion

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The research  found that the viral video does not depict a real-life incident. The footage showing a fighter pilot allegedly repairing an aircraft engine during flight was generated using artificial intelligence and later circulated online as genuine. The accompanying claim that the video was released by Iran's Revolutionary Guards to threaten the United States and Israel is also false.

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Executive Summary

Amid nationwide outrage over the gang-rape of a 13-year-old minor in Sriganganagar, Rajasthan, a video is circulating on social media. The clip shows police officers tying the hands of several accused individuals and parading them publicly on the streets. Users sharing the video claim that these are the culprits from the Sriganganagar case being beaten by the police.

A fact-check by the CyberPeace Research Wing  found this claim to be misleading. The viral video has no connection to the Rajasthan incident; it actually depicts a separate event from Patan, Gujarat, dating back to March 2026.

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The Claim
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On July 7, 2026, a user on X (formerly Twitter) shared the video with the caption: "32 jihadis assaulted, brutalized, and raped a 13-year-old girl for five days. These criminals must get the harshest punishment to set an example."

https://x.com/RakeshKishore_l/status/2074400280352084129 

https://archive.ph/RLJll 

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Fact Check

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To verify the viral claim, keyframes from the video were extracted and analysed using Google Lens for reverse image search. During the research, we found a report published by NDTV on March 19, 2026, which carried visuals matching the viral video. The report link and screenshot are provided below:

https://www.ndtv.com/india-news/gujarat-cops-thrash-18-accused-in-public-during-crime-scene-reconstruction-11238125

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According to the NDTV report, a video showing police personnel publicly assaulting 18 alleged accused persons in Gujarat’s Patan district had surfaced. The incident was reported to have taken place during a crime scene reconstruction exercise.

The report stated that the accused, allegedly linked to an extortion gang, were taken to Chanasma for the reconstruction process. During the exercise, police personnel were seen assaulting them. Witnesses claimed that the accused were paraded through areas where they had allegedly created fear among locals.

The accused were reportedly linked to the alleged Jhiliya gang. The incident occurred days after a violent clash in which members of the same group allegedly attacked a police team, forcing officers to retreat from the spot.

During further research, we found a report published by ABP Asmita on March 19, 2026. According to the report, the incident was linked to an old dispute over temple donations.

The report stated that the accused were produced before a court, which sent them to five days of police custody until March 23, 2026. The report link and screenshot are provided below:

https://gujarati.abplive.com/news/gujarat/patan-farmhouse-violence-case-tied-their-hands-with-a-rope-and-then-patan-police-beat-18-goons-with-button-on-the-road-974702

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Conclusion

The research found that the viral video is not related to the alleged gang rape case in Sri Ganganagar, Rajasthan. The video is being shared with a false context. The footage actually belongs to a separate incident from Gujarat’s Patan district reported in March 2026.

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