For somebody who posts on X or other social media platforms to become recognized by the media and other offline institutions as a significant, influential voice worth quoting, it usually takes patience and hard work to build an audience that respects and identifies with them. There is another way to achieve the same kind of reputation with far less work. According to a research report from the Network Contagion Research Institute, American political influencer Nick Fuentes opted for the second approach, a collection of tactics that made it appear like a huge number of people were amplifying his tweets within half an hour of posting them. While Fuentes wields his influence in the political realm, the tactics he employed are portable and available to people looking for the same quick solution in the business world. In this short midweek episode, we’ll break down the steps involved and the warning signs communicators should be on the alert for.

Links from this episode:

“America Last: How Fuentes’s Coordinated Raids and Foreign Fake Speech Inflate His Influence,” research report from the Network Contagion Research Institute
Eric Schwartzman’s LinkedIn post and analysis of the NCRI’s report

Raw Transcript:
Neville Hobson: Hi everybody and welcome to For Immediate Release. This is episode 493. I’m Neville Hobson.
Shel Holtz: And I’m Shel Holtz, and today I’m going to wade deep into America’s culture and political wars. I swear to you, I’m not doing this because of any political or social agenda on my part. What I’m going to share with you is not a social or political problem, it’s an influence problem. And in communications, influence and influencers have become top of mind.
We’re going to look at the rise of Nick Fuentes’s significance on the social and political stage. For listeners outside the US, you may not know who Fuentes is. He’s a US-based online political influencer and live stream personality who’s built a following around the “America First” ecosystem and has sought influence within right-of-center audiences, including by positioning himself in opposition to mainstream conservative organizations like Turning Point USA and encouraging supporters to disrupt their events. Tucker Carlson has had him on his show as a guest. President Donald Trump has hosted him at the White House for a dinner.
In a recent report that our friend Eric Schwartzman highlighted on LinkedIn—that’s how I found it—the Network Contagion Research Institute (NCRI) asserts that Fuentes is a fringe figure whose public profile rose to a level of significance by manipulating online systems. The NCRI, by the way, is an advocacy group focusing on hate groups, disinformation, misinformation, and speech across social media platforms. It’s been around since, I think, 2008. And they’ve taken their own fair share of criticism for bias, but this report looked pretty well researched, and there will be a link to it in the show notes.
The techniques that Fuentes used to rise to significance are, and this is the key here: If bad actors can inflate the perceived importance of a fringe political figure, the same mechanics can inflate the perceived importance of a product, a brand, a CEO, a labor dispute, or a crisis narrative.
I’ll share the details right after this.
In modern media ecosystems, visibility is often treated as evidence of significance. Of course, when the system can be tricked into manufacturing visibility, it can be tricked into manufacturing significance. Here’s the playbook. The report focuses heavily on what happens immediately after a post is published, specifically the first 30 minutes. That window matters because platforms like X use early engagement as a signal of relevance. If a post seems to be spreading fast, the algorithm acts like a town crier, showing it to more people.
The researchers compared 20 recent posts from several online figures. Their finding was that Fuentes’s posts regularly generated unusually high retweet velocity in the first 30 minutes, enough to outpace accounts with vastly larger follower bases. It outpaced the account of Elon Musk, for example.
The key detail here isn’t just the volume of retweets, it’s the timing. Rapid, concentrated engagement right after posting creates the illusion that the content is taking off, kicking it into recommendation streams. This is the same basic mechanic behind launch day boosting. You’ve seen this for people who have a new book out and they go out to friends and ask them to boost that new book the day it’s released. If you can create the appearance of immediate traction, you can trigger algorithm distribution that you didn’t earn.
In commerce, this shows up as engagement pods, coordinated employee advocacy swarms, and community groups that behave like a click farm. If your measurement system rewards velocity, someone can and will manufacture velocity.
So who’s responsible for those early retweet bursts? Across the 20 posts studied, 61% of Fuentes’s early tweets came from accounts that repeatedly retweeted multiple posts in the same window. In other words, this wasn’t a crowd. It was a repeatable mechanism, the same actors over and over, hitting the algorithm where it’s most sensitive. In business, you don’t need millions of genuine fans to create the signal of traction. You need a reliable, repeatable set of accounts that behave predictably at the right moment. This is why a relatively small number of coordinated actors can distort what public response appears to be, especially early in a narrative when journalists and internal leaders are trying to interpret what’s happening.
The report describes the amplification network as dominated by accounts that aren’t meaningfully identity-bearing. Among the repeat early retweeters, 92% were anonymous. Furthermore, many of these accounts were essentially single-purpose. They existed solely to boost specific messaging. Now, anonymity is a feature, not a bug in manufactured influence. In a corporate context, we see this as sock puppet commenters flooding a CEO’s LinkedIn post with applause or fake grassroots accounts inflating outrage against a policy change. If you’ve ever seen a comment section where the voices feel oddly similar and oddly committed, you’ve seen the symptom.
Perhaps the most operationally important finding involves outsourced capacity. Before a major inflection point in September, about half of the retweets on Fuentes’s most viral posts came from foreign, non-U.S. accounts. The report highlights concentrations in countries like India, Pakistan, Nigeria, Malaysia, and Indonesia. There’s no organic reason for these regions to be driving a U.S.-centric fringe political account. These geographies match known patterns associated with low-cost engagement farms.
If you’ve ever dealt with fake reviews or fake webinar attendees, you understand the market for outsourced attention. It’s snake oil. The same infrastructure used to inflate a political persona can inflate a brand narrative, especially when the goal is to trigger secondary effects like investor interest or the internal belief that everyone’s talking about this.
In the report, Fuentes isn’t presented as a passive beneficiary of an algorithm. The report states that he repeatedly issues direct instructions to followers: “Retweet this. Everybody retweet.” Turning amplification into a synchronized act. If you run employee advocacy programs or franchise networks, you’re already sitting on “raid capability.” The ethical version is mobilizing real stakeholders transparently. The unethical version is instructing coordinated networks to simulate stakeholder response specifically to game recommendation systems.
This is where communicators need to be brutally honest. The distance between campaign mobilization and manufactured consensus can be uncomfortably short.
Fuentes’s final move is the flywheel. Once you’ve manufactured signals that look like relevance, institutions treat those signals as real. The report argues that mainstream media coverage increased sharply after major news shocks, while the persistent manufactured engagement helped keep the subject elevated between those shocks. It also reports a 60% increase in high-status framing of the subject in mainstream articles after that inflection point.
This is classic social proof laundering. Once a narrative appears prominent on-platform, it becomes easier to place it off-platform: press mentions, analyst notes, investor chatter. At that point, people stop asking, “Is this real?” And start asking, “How big is this?”
For business communicators, here are three practical takeaways.
First, treat attention as an attack surface. If a narrative is unusually fast, unusually concentrated, or driven by accounts that don’t look like real stakeholders, assume you’re looking at influence operations.
Second, build signal hygiene into your intelligence process. If your team reports on social activity, incorporate basic credibility checks, like repeat actors, anonymity patterns, and geographic anomalies.
And third, audit your own incentives. If your organization celebrates reach metrics without interrogating provenance, you’re teaching everyone—agencies, vendors, and bad actors—that synthetic engagement is rewarded.
This isn’t just a problem that’s “out there.” The PR and marketing industries have plenty of muscle memory around manufacturing perception. The difference is whether we keep that muscle under ethical control or let the algorithm decide what we’re willing to do. Just because you can manufacture influence doesn’t mean you should.
Neville Hobson: That’s quite a story, Shel. I’m wondering how many people in our profession truly understand how this actually works. Your call to action, as it were, was to pay attention to this and pay attention to that. But I think people need to understand why and the deeper picture surrounding it.
So, for instance, the report—some of which you summarized in your narrative—struck me. And indeed, from the summary I asked ChatGPT to create (that saved me reading the whole damn thing), it was very helpful. According to the report, the researchers said that Fuentes consistently generates extraordinary engagement in the first 30 minutes after posting on X. Early retweet velocity outperforms accounts with 10 to 100 times more followers than he’s got. You mentioned Elon Musk; he’s one of them. When normalized by follower count, his engagement is orders of magnitude higher than comparative political influencers.
Why does this matter? This to me is significant to try and get a handle on this. Platform algorithms heavily weight early velocity as a sign of relevance. So once triggered, content is promoted regardless of whether engagement is authentic. Speed, not scale, is a manipulation lever. This is a critical insight for communicators. Algorithms cannot distinguish motivation, only momentum.
So when people talk about—as they do, and I remember using this 10 years ago as a sign that something is working—”Look at how this thing’s taken off!” This is seriously significant: understanding how this works.
Another part of that is, as you mentioned, the foreign origin engagement—the synthetic catalyst, if you like. Half the retweets on Fuentes’s most viral posts came from non-US accounts, and you ran off a list of countries that are the prime originators of large volume. It says there is no plausible ideological or cultural reason for these regions to be organically amplifying a US-centric white nationalist figure. Makes sense, doesn’t it? So why does that matter? Well, these geographies closely match known low-cost engagement farm infrastructures. So foreign engagement appears to act as a spark, creating the illusion of virality.
And it uses phrases that most people won’t know about—I’m only just getting familiar with it myself—like classic “signal laundering.” You’ve heard of money laundering, right? But now signal laundering. It highlights this coordinated amplification, which is not spontaneous engagement. It’s not enthusiasm spreading naturally, it’s coordination masquerading as popularity.
So I think all of us, as communicators trying to grasp something like this to understand the significance of it, are going to have to spend a little extra time understanding how it all works.
There’s one element that came out that I thought, “Wow, yes, you see this.” I can think of two people I follow on LinkedIn who do this. Illustrating Fuentes in this example is not a passive beneficiary; he actively runs it. The evidence includes hundreds of documented instances where he issues real-time commands on live streams like “Retweet this,” “Everyone retweet,” “Quote tweet it now.” I see people doing that even on LinkedIn. There’s one individual I’m not going to mention—because it wouldn’t be right to do that in this way—who has got thousands and thousands of followers. I was looking back through some of his recent posts and they are full of stuff like that. His email newsletter is nothing but that, actually. These directives align precisely with the early velocity spikes observed in the data, according to the report.
Interestingly, X’s own policies say that this behavior qualifies as coordinated inauthentic activity, platform manipulation, and spam amplification, yet the activity persists on X. So to me, the question for everyone listening is: surely you cannot trust a platform like X with your brand messaging, right? So why are you still there in that case?
It means loads more we could dissect in that context, but I think it’s necessary for people to truly understand how this works before you can understand what to do about it.
Shel Holtz: Yeah, and you asked how many people in our business might actually understand this. I think if you look at a department like mine where there’s two of us and we’re mostly focused on internal communications, this doesn’t hit our radar. But if you’re a marketing agency and you are tasked with elevating a brand, you got to figure that if a 25-year-old white nationalist fringe character on the social-political scene can figure this out, the people running digital media for a mid-sized agency can easily figure this out.
I suspect there are probably YouTube videos telling you how to do this. You sign up with one of those farms in one of those countries that has the instruction to amplify every time you tweet, and you’re off to the races. And as you mentioned from the report, the algorithm can’t really tell the difference.
Now, this is something that I think is in large part on the platforms—whether it’s X or any of the others—to improve their processes so they can identify and block this sort of thing. The idea that you can start to get media coverage, that people will start including you in their reporting because you appear significant as a result of this blatant manipulation—when you really wield no influence, when the people retweeting you have accounts that have been set up just to retweet you—that’s on them, I think. But they’re clearly not doing anything about it. Musk wouldn’t do anything about it. I wouldn’t expect him to. Zuckerberg’s not going to do anything about it. I wouldn’t expect him to. I wish he would, but knowing what I know about these people, I wouldn’t expect them to spend time and money becoming more ethical. It’s just not in their DNA.
So it’s on us. And where I can see this being used in the business context most blatantly is by advocacy groups when an organization is having a crisis. Because who speaks first is the one who gets the traction. Everything else is reacting and responding to that. And if you could get that kind of momentum, that kind of velocity, that kind of visibility for your point of view in opposition to the perspective of the organization experiencing the crisis, then you’re going to win in that crisis. It’s going to be very difficult for the organization, even employing the best digital crisis communication practices, to overcome that kind of a process.
So this is why I think we need to be aware of this. From my perspective, I have my own personal views about Fuentes and the fact that he’s doing this, but that’s not what this is about. This is about the fact that if Fuentes can do it, your opposition can. It might be, let’s say, a union if you’re a non-union company and they’re trying to get a foot in the door. It could be a competitor trying to make you look bad and elevate their own organization as an investment or as a provider of goods or services. All of them can take advantage of this process because it’s possible.
And frankly, once you dig into it, while it seems complicated, it really isn’t. It’s just subscribing to these services, getting everything set up, and then you just start tweeting or posting on LinkedIn or wherever it is, and everything just follows.
Neville Hobson:: Yeah, I think I mentioned LinkedIn the way I did, but X is the serious negative platform, right? But I would imagine most other platforms that are used for business purposes are subject to this manipulation. And it makes you think you need to know more about the places that you spend time and populate and share information about your business.
The report goes into—or rather the interpretation I’ve made certainly—implications for communicators and organizations, or the key takeaways, I suppose, to summarize it all. I mean, you’re right, the report is long, and it would benefit from a simplified executive summary. Maybe what we’ve prepared might help people get a better handle on what to look at.
But some of the interesting things that summarize it: “Algorithms amplify speed, not authenticity.” And that’s what I think most people—and I’ve been guilty of this too—where speed is really the important thing here. The velocity of your message getting out there and going viral, as people still use that term, is what it’s all about. Absolutely, that’s not what it’s all about. And in this particular age we’re in now with artificial intelligence, I’m arguing very strongly that it is not about speed at all. It’s about being in the right place at the right time with the right message, not necessarily being the first or the fastest with that message.
Another point: “Anonymous and foreign networks can manufacture legitimacy.” How do you figure that out? Interestingly, and I agree with this very much so, “Mainstream media mistakes visibility for importance.” Absolutely true in my view. So all these tactics are portable.
And the final point, I suppose—there’s like 20 more I’ve got for now anyway—the real issue is not who used the playbook to do this. It’s how easy the playbook is to use. I think it’s absolutely right. And I think many people would succumb to kind of increased pressure to play the game because that’s what everyone else seems to be doing. But also it throws up, I think, a bigger concern. It’s become harder to measure engagement if what you’re measuring is suspect.
So that adds some big questions on how are you going to proceed from this point on. So:


What signals do you treat as evidence of relevance?


How easily could those signals be fabricated?


Are we rewarding momentum over substance? You need to know the difference.


And where does responsibility sit? Platform, media, or practitioner? Or all of the above?


Those are four questions—there’s probably lots more—but that might not be a bad starting point.
Shel Holtz: I don’t think it would. And I think the more practitioners who become aware of this, those that abide by an ethical code, need to raise their voices because I think the more pressure there is on the platforms, the more they will look to change the infrastructure to address this. If nobody complains or if it’s just people on the fringe like us, then nothing’s going to change.
And you’re right, Fuentes started all of this before the AI revolution. And AI is just going to make this worse with the ability to create those posts that get amplified because you have manipulated the system the way Fuentes has. So I’d like to see people kind of raise their voices. Maybe professional associations need to start advocating on behalf of fixing this. You know, AI has led a lot of people to talk about authenticity more than we already were, and we already were a lot. And if authenticity matters, then I really do think we need to raise our voices and demand change from the platforms so that people can’t do this.
Neville Hobson: I agree.
Shel Holtz: And that’ll be a 30 for this episode of For Immediate Release.
The post FIR #493: How to (Unethically) Manufacture Significance and Influence appeared first on FIR Podcast Network.

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