Power Laws in Culture

Why Hits Will Persist in an Infinite Content World

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• Almost 20 years ago, Chris Anderson wrote The Long Tail, which accurately predicted that the Internet would fragment attention and consumption would shift into the “tail.” But Top Gun Maverick generated over $700 million at the domestic box office last year, Bad Bunny had 18.5 billion streams on Spotify last year and 142 million households reportedly watched Squid Game Season 1 in its first 28 days. Why are there still hits in a fragmenting world?
• I recently posted an essay called Forget Peak TV, Here Comes Infinite TV. It made the case that over the next decade video will follow the path of text, photography and music and the quality distinction between “professionally-produced” content and “independent/creator/user-generated” content will increasingly blur. This will result in practically infinite quality video content. Will there still be hits then, or only personalized niches?
• Have you ever wondered why so many blockbuster movies are about superheroes? Is Hollywood lazy or are consumers’ tastes becoming dumber and more homogenized? Or neither?
• Why does something go viral, anyway?
• Do content recommendations push you to the most popular shows, movies and songs or are they tailored just for you? Or do they have a different agenda?
• Will web3 really be the savior of small creators?
• When Billie Eilish, Lil Nas X, Mr. Beast or PewDiePie emerge from obscurity, was it inevitable that their talent would be recognized or just luck?
• Are the top rated reviews on Amazon or answers on Quora really the most helpful?

All of these are questions about the distribution of popularity. And the same phenomenon underlies the answers: networks.

This essay may be a little wonky, but the topic is something I’ve been thinking about for more than a decade. (Off and on, not continuously.)

I explain why power law-like distributions — meaning a few massive hits and a vast number of misses — are an inherent feature of networks; describe how recommendation systems can either dampen or reinforce social signals; show some examples of the persistence of power law-like distributions in media across movies, TV, music and the creator economy; and discuss why all this matters.

Tl;dr:

• In an apparent contradiction, the Internet both fragments and concentrates attention.
• The reason for the former is intuitive. More stuff, less attention per unit of stuff. The reason for the latter is not. It happens because networks are subject to powerful positive feedback loops. On a network, people’s choices are influenced by others’ decisions, amplifying “hits.”
• There are two mechanisms underlying this: information cascades (when people treat others’ choices as signals of quality) and reputational cascades (when people conform with the group decision). As choice has exploded on the Internet and it has become easier to both observe others’ choices and share your own, these mechanisms have become more powerful.
• Consumers also rely heavily on recommendation algorithms to make choices, intentionally and unintentionally. Depending on how they’re constructed, these systems can either boost or dampen the social signals arising from the network.
• The result is that the distribution of consumption in almost all media persistently, and in some cases increasingly, looks like a power law: a few massive hits and a very, very (very) long tail. I provide a framework for thinking about the “extremeness” of the distribution and show a few examples: box office, Netflix original series, Spotify streams and Patreon patrons.
• There are a number of important implications for media companies. The good news is that there will likely always be big hits, even in a world of practically infinite content. The bad news is just about everything else: the lucrative middle is being hollowed out; the randomness — and therefore risk — in producing hits is climbing; the tail is become more competitive for hits; more economic rent will likely shift to talent; content producers are increasingly at the mercy of curators’ algorithms; and paid media is being devalued.

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