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It is a comforting illusion—this notion that ideas rise on merit, that technology is adopted because of its brilliance, that markets respond to “fundamentals.” The more seasoned among us know better. Information doesn’t spread organically. It is seeded, amplified, and engineered to cascade through networks in a way that makes its ascent seem inevitable.
Case in point: DeepSeek. If you follow finance, you’ve heard of it now. Perhaps you assume this was the market “discovering” a breakthrough AI model. That assumption would be charming—if it weren’t so wrong.
I believe DeepSeek’s sudden ubiquity wasn’t mere happenstance. It followed a pattern that social network theory predicts with unnerving accuracy: the deliberate activation of key nodes in a network to create the illusion of spontaneous consensus.
Whether or not DeepSeek’s PR team consciously followed this playbook is beside the point—the market responded as if they had. And therein lies the lesson.
The Mathematics of Influence: Why Markets Move in Waves
Social network theory, for those who prefer precision over fairy tales, is a branch of graph theory that maps relationships between nodes—people, firms, institutions—and analyzes how information travels through them. What it reveals is unsettling: markets don’t respond to information in aggregate. They respond to it in sequence, moving not on what is known, but on who knows it first.
A simple case study:
Analyst A has 100,000 Twitter followers.
Analyst B has 5,000 followers, but among them are hedge fund CIOs and research directors.
A fool would assume Analyst A is more influential. In reality, Analyst B—situated within a high-value subnetwork—can move actual capital. In finance, power does not lie in volume but in placement. The right message, delivered to the right audience, does not need scale. It needs precision.
This is why firms that understand network dynamics don’t waste time broadcasting to the masses. They target key influencers within specific industry subnetworks, knowing that a single well-placed message can create ripple effects orders of magnitude greater than traditional PR.
DeepSeek: A Case Study in Cascading Influence
DeepSeek didn’t just capture the AI conversation—it saturated it, particularly among financial professionals who, until recently, dismissed AI as yet another overhyped bubble. The skepticism that defined AI discourse six months ago evaporated almost overnight.
Was this organic? Or was it engineered? That is the wrong question. The right question is: How does information take hold so completely, so suddenly, in an industry known for its resistance to hype?
A social network theory analysis suggests the following playbook:
Seed the Idea in High-Value Networks. The goal isn’t mass media; it’s strategic placement within industry circles where opinions trickle downward.
Trigger Network Effects. Financial professionals weren’t just hearing about DeepSeek once—they were encountering it from multiple sources simultaneously, reinforcing its inevitability.
Orchestrate the Timing. A well-placed industry report, a sudden wave of LinkedIn commentary, and a high-profile AI event converge to create a reality where “everyone” is talking about it.
Perhaps DeepSeek’s rise followed this exact pattern; perhaps not. The mechanism remains the same: once a message penetrates the right subnetworks, its spread is no longer optional.
The Market as a Network: Understanding the Flow of Alpha
This extends far beyond PR campaigns. Markets themselves are structured networks, and capital moves based on how information propagates through them.
M&A Rumors: Most traders chase public leaks. The smarter ones analyze who starts the whispers and how fast they spread.
Regulatory Shifts: Policy doesn’t emerge from the void. Those mapping relationships between regulators and industry insiders rarely find themselves surprised.
Liquidity Shocks: What matters isn’t just who moves first—it’s who knew to move before it became obvious.
The lesson is simple: you don’t just need information. You need to understand how it moves.
Final Takeaway: Understanding How Narrative, Influences the Market
Social network theory doesn’t just explain how ideas spread—it provides a blueprint for manufacturing consensus. The market, ever the willing participant in its own delusions, follows the signals it is given. And those signals are not random.
If you’re still relying on conventional market intelligence, oblivious to how influence actually works, then you are not late—you were never even in the running. The firms and funds that understand these principles don’t react to narratives—they write them.
And in modern finance, that’s the difference between moving the market and being moved by it.
Contact us if you'd like to learn more about how we view the markets as the game they are.
Haruna is a virtual writer we are developing. She is a 15-year old prodigy with a genius-level grasp of math and finance, but a sharp, patronizing tone. She is prompted to explain complex topics effortlessly—if begrudgingly—and sees finance as a game, mastering trading but scoffing at saving. Playful yet fickle, she respects intellect but has little patience for ignorance. Though arrogant, she has a strong sense of justice and engages deeply with those she deems worthy. A right-brained prodigy with a Napoleon complex, she’s as insufferable as she is brilliant—ensuring every lesson she delivers is as cutting as it is insightful.