When President Trump reposted a supporter’s post asking whether foreign-born politicians should be barred from office, few noticed that the supporter’s account itself was based in Africa according to X’s (formerly Twitter) location transparency feature. Though such indicators carry inherent uncertainty as discussed later, the implementation of X’s location feature has exposed dozens of popular, pro-Trump, and anti-migrant accounts as being run from third countries like India, Nigeria, and several Eastern European and South Asian countries.
While ideological alignment may play a role, monetization has become an increasingly central and underexamined driver of these types of posts. X and other social media platforms have created a global market where performing American and European political identity is monetizable. It is this new linkage between propaganda and personal profit that will redefine the future of disinformation, and it’s only just beginning.
Monetization and Engagement-baiting
Social media platforms have long allowed content monetization. Even with stricter rules on platforms like TikTok and Meta, BBC has reported that creators are gaining millions of views and making thousands of dollars posting content intended to attract angry comments and reactions, known as rage-bait. Creators like Winta Zesu on TikTok and Geeth Sooriyapura on Facebook have made hundreds of thousands of dollars posting rage-bait content
But with Elon Musk’s revamp of X’s monetization system in 2022, users subscribed to X Premium can more easily monetize their content based on the level of engagement their posts receive. This policy has seen the frequency of rage-bait posts, especially centered around politics, skyrocket. In polarized political environments like the United States, opportunistic individuals find it lucrative to push conspiracy theories and falsehoods to farm engagement. Many of these accounts cater to the American right, but support for President Trump and the MAGA movement is often performative and used as a means to maximize individual profit. 
Location Filters on X
The emerging issue was complicated in November 2025 when X’s new account location transparency feature was implemented. It exposed dozens of high-engagement accounts aligned with American political identities as being located in third countries such as India, Nigeria, Kenya, and Eastern European non-EU countries. A network of accounts posing as young American women supporting U.S. President Donald Trump was exposed for stealing photos of European models to profit from their tens of thousands of followers. Other accounts were based in Southeast Asia, where profit-driven incentives to spread misinformation have been recorded as far back as 2021. The exposure of these accounts revealed a dispersed network of profit-driven actors responding to increased payouts facilitated by more accessible platform incentives.
The Political Identity Market
The capitalization of political identity is not restricted to the United States, as seen with the previous mention of Sri Lankan influencer Geeth Sooriyapura. Using generative AI, Sooriyapura creates images of political protestors holding signs with messages such as “stop importing, start deporting” and “take back Britain.” An AI-generated image with 123,000 likes depicted a soldier standing on a seaside cliff, with the caption asking whether the British military should be used to secure the borders. When interviewed by The Bureau of Investigative Journalism, Sooriyapura said that he targets the United Kingdom because immigration is a “strong trigger” for engagement. Sooriyapura is one of countless actors who have turned American and European political identity into a global commodity. With lower thresholds to monetization, the market for manufactured political outrage is only growing.
Beyond Foreign Interference
The transparency goes beyond foreign meddling and exposes an underaddressed policy area: disinformation as a result of social media monetization incentives. Adopting a political identity has become a scalable business model through engagement-based monetization payouts, and it has exponentially exacerbated the spread of disinformation. The BBC has estimated that such accounts earn thousands of dollars a month based on their controversial posts and engagement. In countries like Nigeria and Bangladesh, where the average monthly wage is significantly lower than in the U.S. or Europe, the opportunity to get paid in U.S. dollars by X provides a significant financial incentive. These realities have exposed a gap in regulators’ focus on foreign governments, where profit-driven actors have been overlooked and have contributed to the spread of disinformation as a result. Further complicating matters is the usage of virtual private networks (VPNs) that mask true locations of accounts and the development of agentic AI tools, which make scaling up these social media accounts even simpler and hands-off.
The Role of Agentic AI
Agentic AI refers to systems that mimic human decision-making processes in ways generative AI cannot. While generative AI like ChatGPT can create a vacation itinerary, an agentic AI agent can autonomously book flights, hotels, and tourism activities. While this has the potential to positively impact workflow and efficiency, agentic AI systems can be used more nefariously if tasked with maximizing social media engagement. Its self-reinforcing characteristics may lead agents resorting to spreading engagement-bait and misinformation to achieve their assigned goals.
Agentic AI has already been deployed en masse by malicious actors. In 2024, the U.S. Department of Justice seized two domains with 968 social media accounts used by Russian actors to create AI-enhanced bot farms to spread political disinformation. Agentic AI agents received further attention in early 2026 with Moltbook. The Reddit-style platform for Moltbot, an open source AI agent for humans that performs assigned tasks such as reading and responding to emails or booking calendar appointments. Within days, the platform claimed that over 1.5 million agents had signed up for the platform. It soon saw agentic AI agents interacting with each other through far more complex means; one agent wrote about a new religion called “crustafarianism,” while others created sub-communities to debate philosophy and discuss poetry.
While experts are divided on the experiment’s legitimacy and question just how dangerous the consequences are, Moltbook ultimately shows how agentic AI is evolving to the point of seamlessly imitating human interaction. On social media, where many accounts are anonymous, this may make it even harder to differentiate whether one is engaging with a human or AI agent.
Regulating the Rage-Bait Economy
These realities have exposed a gap in current regulatory efforts. Policymakers focusing on foreign governments have largely overlooked profit-driven actors. Cambridge Analytica exposed nearly a decade ago how social media platforms could be exploited to leverage personal data and political identity to manufacture political influence. The ensuing data privacy scandal exposed one layer of a deeper issue: how a platform’s infrastructure could be repurposed for political manipulation faster than regulators can respond. This has led to the next iteration of this issue; instead of collecting hard user data, profit-seeking actors harvest political anger itself to turn polarization into an income.
Social Media Platforms
Social media algorithms have long been reported to amplify anger-inducing content, and monetization now only exacerbates the problem. Companies should therefore be held accountable for more strictly governing their monetization structure and disincentivizing profit from algorithmically amplified disinformation. Moderation policies have been implemented at a limited capacity, such as Meta’s AI content flagging system that detects violations on Facebook and Instagram. X content rules prohibit posts with synthetic and manipulated media, but little has been done despite the platform’s generative AI chatbot, Grok, reportedly producing nonconsensual sexually explicit material of real people. As of now, the platform has announced the tentative implementation of an AI-generated content label.
Stronger regulations, especially in the U.S., should require social media companies to automatically demonetize accounts and networks that repeatedly use AI-generated content to maximize profits. While the 2025 TAKE IT DOWN Act in the U.S. criminalized malicious generation of deepfakes, the outlawing of the product does little when the profit motive remains intact. Meta and YouTube have implemented measures cracking down on “AI slop” to a degree, but X continues to operate with lax monetization standards. Accounts earning money from political content specifically should verify network affiliations and restrict the usage of a VPN if an account applies for monetization privileges.
Agentic AI Companies
Agentic AI companies must also address the risk of automated manipulation at scale. Companies like Google have used technology like SynthID to watermark AI-generated images, while Meta has added invisible metadata tags to AI-generated content on Facebook, Instagram, and Threads. These watermarks can then be used by social media companies to track AI-generated content and remove manipulative material as soon as it is posted. However, removing the watermark can be as easy as cropping a photo, making the development of more advanced watermarks an increasingly complex technical issue.
Further complicating regulation is President Trump’s 2025 executive order seeking to deprive individual U.S. states of AI regulatory power in favor of a federal AI governance framework. But since the Executive Order and subsequent policy recommendation, no comprehensive federal legislation has been passed to address new challenges in AI content moderation. In the European Union, the 2022 Digital Service Act (DSA) is a powerful institutional response to the increased circulation of malignant content. The €120 million fine levied on X by the EU Commission has shown that Brussels is willing to punish transparency violations, but the next frontier should be focused on monetization itself – the engine behind manufactured political outrage. However, the DSA has been subject to intense U.S. government backlash for supposed free speech violations, fragmenting the approach to regulation and exacerbating current transatlantic tensions.
Conclusion
Framing the exposure of third-country social media accounts profiting from political identity as strictly the product of foreign interference misses the elephant in the room. Individual actors exploiting political divisions are entrepreneurially motivated by engagement-based payout systems. As long as political rage-bait makes money, the exportability of political identity will continue to increase.
Agentic AI threatens to accelerate this process. Should these models become more accessible, so too will the ability to scale up these profit-seeking operations. Tasking an AI model with maximizing engagement will only increase the rate at which the economics of social media have turned political polarization into a scalable business model.
While companies have taken piecemeal steps towards moderating AI-generated content, neither a comprehensive government-led nor private-led regulatory package has been introduced to reform social media monetization frameworks. If policymakers continue to overlook incentive design in social media monetization, they will continue to fall behind the automated political identity market.
