Tag: Carousel

Netflix versus Crazy Rich Asians: What Else Does Netflix “80 Million Customer Accounts” Tell Us?

(For Part I of this series on Netflix versus Crazy Rich Asians, click here.)

If you can’t tell by my article last week, I had a lot of fun with my comparison between Netflix romantic comedies and Crazy Rich Asians. Unfortunately, I had a lot of ideas for that article that hit the cutting room floor. 

Some because they were too speculative, some to save room, and some to make a tighter narrative. (I had tried a long shot publication at a bigger outlet.) And some because I couldn’t prove them. So for a respected publication, it didn’t make sense.

But this is my website. I’m free to make all the speculation and ask all the tough questions I want to here. Since Netflix only provided me one number—80 million customer accounts watched an original romantic comedy the last summer—well, I want to ask that number a lot of questions. I want to interrogate that number to within an inch of its life. So that’s what I’m doing today. Asking—and answering—all the other questions inspired by this comparison.

What other “circumstantial” evidence did you leave out?

A few pieces, but one major one. Essentially, the major studios stopped making romantic comedies for two reasons. First, they don’t have a high enough “ceiling” in that they don’t ever tend to have billion dollar movies. Second, and crucial for our math, is that they also don’t tend to perform well overseas. This applies generally to all comedies. Comedy is a local phenomena so it’s rare for comedy films to do well overseas unless they are very, very broad. (Some of the broad sitcoms like The Big Bang Theory or Simpsons do travel. Others, I’ve heard, don’t.)

We’re seeing this right now. Aquaman is the number one movie in the world…and it didn’t open in America. Crazy Rich Asians, meanwhile, flopped in China. To show this effect, here’s some data. For my series on Disney’s Lucasfilm acquisition, I made a data set of 50 “franchise” movies. These provide a good set of comps for comic book movies and their ilk. As you can see, franchises now see 63% of the total box office come from overseas (and even this still includes a lot of old Star Wars and Indiana Jones data.)

Blockbuster TableNow compare that to romantic comedies. I don’t have as large a list, so I pulled some sample romantic comedies. The trend is clear…

RomCom US Inter Splits

Four recent romantic comedies that did “well”, had over 70% of their box office come from the US market. Crazy Rich Asians, notably, only had 22% of its total box office come from overseas. Compare that to massive blockbusters like Avengers or Pacific Rim, where over 66% or 75% of their box office came from overseas.

This has implications for Netflix. Mainly, three facts collide that can’t all be true simultaneously: 

– Netflix had 80 million customer accounts watch an original romantic comedy last summer.

There are 60 million US customer accounts. (Rounded up slightly.)

– US romantic comedies tend to have 60-40 splits in US to international viewing, sometimes as high as 70-30.

This puts us in an awkward place when it comes to the Netflix number. Based off Crazy Rich Asians and other romantic comedies, I could easily assume 60% of the viewership was US based. That leads to some really tricky “consultant math”. Go with me on these assumptions:

– Assume 60% to 40% domestic to foreign split on Netflix romantic comedies

– Assume 1.4 “viewers” for every Netflix customer account.

Black Panther sold 76 million tickets in the United States.

– Assume 15% rewatch rate for Black Panther. 

Here’s those assumptions, now it table form:

Screen Shot 2018-12-11 at 3.41.39 PM

Now, even worse than Netflix claiming it beat Crazy Rich Asians, if we take some conservative assumptions, more people watched a Netflix romantic comedy than the biggest movie in the US last year (Black Panther). Do you honestly believe that?

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Did More People Watch Crazy Rich Asians or a Netflix Rom-Com Last Summer?

The romantic comedy is dead. The highest grossing romantic comedy this year is Crazy Rich Asians, which at $174 million in domestic box office pales in comparison to behemoths like Black Panther ($700 million domestic box office), Avengers: Infinity Wars ($678 million), Incredibles 2 ($608 million) and Jurassica World: Fallen Kingdom ($416 million). Who shall return the romantic comedy to glory?

Netflix. Because of course Netflix.

This summer, Netflix released a series of romantic comedies it dubbed, “the summer of love”. In a letter to shareholders, Netflix celebrated their success. Here’s Vox writing about a particular fact Netflix provided:

This summer, Netflix invested in resurrecting the mid-budget romantic comedy, acquiring movies like Set It Up and To All the Boys I’ve Loved Before for what the streaming service branded as its “Summer of Love.” And now, it’s looking like the gamble paid off: Variety reports that more than 80 million subscribers watched one of the 11 rom-coms on the Summer of Love slate, according to Netflix’s quarterly earnings report.

Vox wasn’t alone in singing Netflix’s praises. They were joined by Variety, Screen Rant, The Ringer and others to write an article on Netflix’ new found success in romantic comedy. All using one “datecdote”, a term I coined yesterday.

In our hurry to constantly keep up with the news, we let little tidbits like Netflix’s above fact wash over us and move on to the next story. So let’s pause and reflect on the fact Netflix revealed. Does this fact seem true? Since Netflix didn’t provide a comparison, I will:

Did more people around the globe watch Crazy Rich Asians or a Netflix Romantic Comedy last summer?

It’s a tough question, isn’t it? If you answer that more people saw a Netflix romantic comedy, then why did the media spend so much time on the phenomena of Crazy Rich Asians? But if you think more people saw Crazy Rich Asians, then how can Netflix numbers possibly be true?

Streaming video companies, like Netflix, have a lot of data, a lot of ways they can manipulate that data, and, most crucially, a lot of data they just don’t give the press. But we can learn a lot about how movies are distributed and judged in today’s media landscape by trying to answer that tough question with the data and facts we do have.

So let’s do our best to get some answers.

How Many People Watched a Netflix Romantic Comedy?

On the surface, this is fairly straight forward. Netflix in their letter to shareholders—a document submitted to the SEC, so a legally-binding, carefully vetted document—used this phrase:

More than 80 million accounts have watched one or more of the Summer of Love films globally.

Netflix chose two words very carefully in the above sentence. First is “accounts”. Not “profiles” or “viewers” but accounts, since this is the only unit of measurement Netflix knows for sure. They know that because they have one account per credit card. I’ve seen this called “users” or “customers” at other companies. 

By definition, this is the floor for the actual number of people who watched a romantic comedy on Netflix. If two people watched a film together, well they still only count as one “account”. If two different profiles under the same account watched, they would still probably count as one. (It’s unclear.) If someone shares their password with someone else, but they use the same profile, that still counts as one view.

If account is a precise definition, “watched” is a term so loose that it could mean anything. For instance, Netflix could count as “watched”, a person who only watches ten minutes of a film and turns it off. They could only count as “watched” people who watch greater than 80% of a film, either by run time or who watched past the 80% point in the film. We just don’t know.

What we don’t know dwarfs what we little we do know. We don’t know how many total hours of romantic comedies were viewed. (Netflix, interestingly, loves to cite this number to describe how popular their platform is, but choose not to provide that fact here. For example, they released earlier this year that they had 350 million hours viewed in one day in January.) We don’t know where people watched—this is a “global” number—or even when. While presumably over the summer, it likely wasn’t a hard three month window.

How Many People Watched Crazy Rich Asians?

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Don’t Kill Mickey Mouse! A Simple Solution to Copyright Law EVERYONE Will Love

Let me paint a nightmare scenario:

“Evil corporations realize they have extremely valuable intellectual property. Famous characters like Superman, Batman, and most of all, Mickey Mouse. These corporations employ armies of lawyers and lobbyists and they get to work on Congress. They extend the copyright on all works indefinitely. This means potentially millions or tens of millions of works that could enter the public domain…never do.

Creativity dies.”

Now imagine the other side:

“Mickey Mouse enters the public domain. There is a flood of Disney merchandise on the market. Evil companies have him start doing pornography. Disney loses billions in market capitalization.

Mickey Mouse dies.”

Scary stuff, right? It’s a classic dilemma. Either we radically improve copyright law and free creativity and Mickey does pornography—what the Electronic Frontier Foundation wants—or we keep the status quo forever and creativity is permanently stifled—what The Walt Disney Company wants.

If I haven’t written it before, I hate dilemmas. Not the idea of having to choose between two bad options, but the concept of dilemmas. Usually “either or” ethical scenarios are the stuff of lazy polemicists. They force someone’s opinion on you by making it seem inevitable.

The above two scenarios do that perfectly. Nightmare scenario one is corporations run amok, ruining creativity for the rest of us. Nightmare scenario two feels better to me, but is still pretty yucky. I don’t want Mickey Mouse in pornography either.

Neither side will win. Again, the “free the content” folks—who I’ve mostly heard on On The Media or read in blogs—have great points about creativity. But being an absolutist on this issue will just drive them into the brick wall of giant corporations with billions on the line. They will NOT give up without a fight. As a result, the corporations have taken the hardest of hard lines. As a result…

Copyright protection dates back to 1923.

To quote TV pitch men, there has to be a better way.

Think about that, for 150 years of American history, copyright extended for a creators live, then it absolutely froze at an arbitrary date that happens to protect Mickey Mouse and Winnie the Pooh. As long as that is the case, we can’t push the copyright law forward in time. Disney won’t let us.

The key to break through the logjam is to understand the true losers. One of my themes of this website will be “understand the economic incentives.” Most problems are clarified, if not solved, when you do this. So while there could be lots of winners by improving copyright, there are some clear losers who will fight this tooth and nail. The studios like Disney, Warner Bros. and others could hemorrhage billions in market capitalization.

So what we need a compromise. We need to realize that the two positions staked out currently in the debate are NOT the only two positions we could have. We could craft a proposal that will free millions of creative works from copyright jail, while allowing Disney and the studios to keep control of their IP, and we can do it for free. In fact, we’ll make some money on it. So here it, trying to get it to fit onto a post card to make Paul Ryan happy:

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NBA-to-Entertainment Company Translator: Part III “The Rest”

(Read Part I and Part II here and here.

The only downside of my NBA-to-Entertainment translator was that I only had 30 NBA teams to unleash my snark. In entertainment, we have many more companies that just couldn’t make the cut. So I had to expand the world of the NBA just a little bit to fit in a few remaining “just too perfect to exclude” translations.

Here you go: the Rest.

The G-League – Discovery (Scripps) and A&E Networks

I’m a hard core basketball fan like many people. But if you asked me to tell you how many teams are in the G-League, I couldn’t do it. (It turns out there are 27.)

I follow entertainment pretty closely. I couldn’t tell you how many channels Discovery (with Scripps post acquisition) and A&E Networks have either. So I looked it up:

19! For just Discovery (with Scripps).

10! For A&E.

That’s more than I would have guessed for both, and you know what, that gives these two a lot in common. Sure, they have a lot of channels/teams you can’t name, but they keep doing their thing. (The difference is a lot of Americans still watch a lot of these channels, which can’t be said for the G-League.)

LeBron James – Marvel Studios

Not the whole enterprise, just the part run by Kevin Feige. Consider these fun connections:

Both LeBron and Marvel started making waves in the early 2000s. Spider-man and X-Men made a lot of news, and you could tell something was brewing, just as LeBron was being called the greatest high school prospect in the world. Marvel Studios released the mammoth hit Iron Man in 2009, the first year LeBron won the MVP. Marvel Studios released the mammoth world building Avengers in 2012, the first year LeBrown won a championship. In 2014, nobody thought LeBron would leave Miami, but he did, and no one thought Guardians of the Galaxy would be a smash hit, but it was. Either way, both LeBrown and his 14 straight All NBA appearances is the equivalent of Marvel Studios launching all successful films since 2009.

In the present times, LeBron coming to the Lakers was the event of the season, like Black Panther or Avengers: Infinity War, take your pick.

Yet, the questions remain for the future. Can LeBron’s health last? Will Kevin Feige keep churning out the hits? So enjoy the ride of Marvel Studios and LeBron while it lasts.

The ABA – 21st Century Fox

Their spirits live on! The ABA brought us the Brooklyn Nets, Denver Nuggets, Indiana Pacers and San Antonio Spurs. And 21st Century Fox will live on in Avatar and Spider-Man.

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Disney-Lucasfilm Deal Part VIII: The Theme Parks Make The Rest of the Money

(This is Part VII of a multi-part series answering the question: “How Much Money Did Disney Make on the Lucasfilm deal?” Previous sections are here:

Part I: Introduction & “The Time Value of Money Explained”
Appendix: Feature Film Finances Explained!
Part II: Star Wars Movie Revenue So Far
Part III: The Economics of Blockbusters
Part IV: Movie Revenue – Modeling the Scenarios
Part V: The Analysis! Implications, Takeaways and Cautions about Projected Revenue
Part VI: Disney-Lucasfilm Deal – Television
Part VII: Licensing (Merchandise, Like Books and Comics and Video Games and Stuff))

If you’ve been reading along after 47 pages and six months of writing, you know that Disney more than made its money back on its purchase of Lucasfilm through releasing wildly successful Star Wars sequels, and then making another $1.7 billion in licensing revenue. So they made their money back.

But to truly get a great return on investment—as I wrote in the introduction in my “gut” section and again when referring the licensing & merchandise—theme parks are the whipped cream and cherry on top. In 2019, if it stays on track, in Disneyland and in Disney’s Hollywood Studios, Disney will open Star Wars: Galaxy’s Edge, which have been under construction since 2016.

And they could be huge money makers.

Theme parks allow The Walt Disney Company to make more off its IP than any other studio. (That’s its competitive advantage.) So let’s figure out how to quantify that benefit. Then, we’ll figure out the costs.

The Challenge: Disentangling the Marginal Benefit of new Theme Parks

With movies, calculating the revenue is messy, but we have lots of data. With toys, forecasting the revenue is easy, but we have way less data. What about for theme parks? In this case, the toughest part of the process is assigning the value.

Think of it like this. We know that putting in a Star Wars: Galaxy’s Edge at Disneyland will drive attendance and revenue. The problem with theme parks is untangling how much revenue they will drive.

In other words, the “marginal benefits”.

Some day I’m going to write “Marginal Benefits Explained!” because it’s a core economic principle—the core principle?—and I’ve seen 7-figure-earning business execs screw it up. Marginal benefits are the additional revenue a business generates by changing an input. So if you’re making a million dollars a year and raise prices, and it goes up to $1.2 million, your “marginal benefit” for the price raise is $200K, the additional revenue you generated.

(You want to know my biggest frustration/pleasure with this website? Every time I write a new article, I think of two more posts to write inspired by it. The “hydra problem” of the Entertainment Strategy Guy.)

This idea is what stymies the analysis with theme parks. Let’s visualize it with an example.

Next year, I’ll walk into Disneyland in the off-season (probably September-ish). I’ll be wearing a Star Wars shirt. My brother will probably rock a Marvel shirt. That said, I’ll also have a three year old wearing, if current trends hold, either an Elsa (Frozen) or Belle (Beauty and the Beast) dress.

So how much of that trip do you allocate to the opening of ? (Punctuation side note: do you italicize theme park lands? I did, but should I?) My family already averages one trip to Disneyland every year, and my daughter knows that Mickey lives at Disneyland. So she’d go anyways. But what about me? I’ll definitely go to see the new park at some point. We could make an analogy of a theme park to a content library on a streaming platform. People pay for the whole thing, not the parts. With content libraries—which is essentially what a theme park is—untangling and clarifying the value offered by each piece can be tough.

The Economics for Theme Parks

When in doubt, I like to boil things down to a simple formula. So let’s do the rough “business model” for a theme park. I came up with this:

Slide63

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NBA-to-Entertainment Company Translator: Part II “The Western Conference”

In the heyday of Grantland, they featured a piece from the good people at Men in Blazers to develop an “NBA to English Premiere League” translator. It helped novices to soccer pick a team in the most popular sports league in the world. It worked so well, I adopted Chelsea as my premiere league squad based off this little comparison to the Lakers:

“Your winning tradition has been soiled by an arrogance which, real or imagined, has caused you to be roundly despised across the league. You have a young coach attempting to gain the respect of a veteran squad, led by a soft Spanish big man and an aging Kobe, who could be any one of Chelsea’s graying superstars — John Terry, Frank Lampard, or Didier Drogba — attempting to substitute experience for pace.”

In 2011, that made a lot of sense. So if you want to pick an NBA team based off where you work, or want to invest based off your favorite NBA team, well I have you covered.

On to the Western Conference. The one with all the stars, all the hits, all the buzz. The “Bestern” Conference. Of course, they still have some teams near the bottom, just not as many.

Western Conference

Sacramento Kings – Spectrum

Let’s just pull the band aid off this wound: the Sacramento Kings are the worst team in the NBA (and have been since the Lakers beat them fair and square in the early 2000s) and Spectrum is just the worst. Honestly, if someone loves “Spectrum” (previously Time-Warner Cable) send me a message.

I’ll wait. Just like a Spectrum customer on hold trying to cancel.

So to “rebrand” Time-Warner became Spectrum a few years back. They said it was because of a merger, but mainly it was to hide from their past. The Kings changed from the Royals because they moved cities, and wanted to hide from their past.

Also, like T-Mobile failing to merge with AT&T, Time-Warner Cable was almost purchased by Comcast, and instead was purchased by Charter Communications. Those set of moves are the NBA equivalent of drafting Boogie Cousins and Willie Cauley-Stein because they were “buddies”, while trading a lot of future draft picks to Boston.

(Yes, I know Spectrum co-owns the Lakers channel. They still are awful.)

Phoenix Suns – AMC Networks

The Phoenix Suns in the 2000s were the flashiest thing in basketball. The “7 seconds or less” teams featured passing & shooting, running & gunning, and won the hearts of NBA pundits, the equivalent of critics. They set the template for pace & space all that would come in contemporary basketball.

AMC Networks won the hearts of critics repeatedly over the same time frame. Breaking Bad, Mad Men, Better Call Saul and even more obscure shows (Halt and Catch Fire; everything on Sundance TV) were the cultural equivalent of Steve Nash, Joe Johnson and Andre Stoudemire. (Nash is Breaking Bad; Shawn Marion is Mad Men; Amare Stoudamire is the rest of the obscure shows, cause he’s career ended too soon and so do they.)

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The Most Important Shape in Entertainment Part III: The Examples

(This is Part III for a multi-part series on “Logarithmic Distribution of Returns”. Read Part I HERE and Part II HERE.)

I come across the flaw of averages in reporting quite a bit. Take my article on MoviePass. The CEO said in an interview with The Indicator that the “average MoviePass customer sees 1.7 movies per month”.

If you read my articles from a few weeks back explaining distributions—and I know you read all 3,000 words—that average of “1.7” is virtually meaningless. He could have told us what the distribution looked like, but didn’t. And probably for good reason. (Impending bankruptcy.)

Since he won’t tell us, here are my guesses:

Chart 1 MoviePass

I would call this a “Log-ish” distribution. First, it’s not a continuous range. With MoviePass, they had discrete scenarios. You see one movie or two movies, but not 2.5. Also, my guess is more people use the service in a given month then let it sit idle, which keeps this from being a true log distribution. I also put an artificial cap at 10 films. That said, the behavior in general will have power-law results. (Some very small number of people will see an order of magnitude more movies over a year, literally 100 in some reported cases.)

(If these numbers were true—and I have no reason to expect them to be—then MoviePass would lose, on average, $5 per month per customer, on average. Given they had 3 million customers when I got my 1.7 number, this would put losses at 15 million per month. Since their CEO said that they were losing 21 million per month, my gut says that tickets were more expensive than my model, mainly because they were over-indexing on coastal users. Also, if the subscribers went up to 4 million, I’d be about perfect.)

Still, I found a Logarithmic Distribution in a random place. (Said in the voice of Rhianna to the tune of “found love in a hopeless place”.) When I started this three part series, I called the Logarithmic Distribution of Returns the “most important shape” in entertainment. I said it applied EVERYWHERE, not just to movies.

Well today, I’ll show you the everywhere. I’ll be blunt with you, I want to convince you of two things:

1. This is the reality of returns in every field of entertainment.
2. The average sucks (or is “sub-optimal”) at describing this reality.

Data Notes and Cautions

Some cautions on data, as always. Why do I always talk about the data itself? Like why provide this critique of my data? Because NO ONE else does on the internet. You should always be as informed, especially when coming with numbers, so when I use data I want you to know what I do and don’t have, what I can and can’t prove.

Caution 1: I’ve seen this in more places than I can share.

I worked at a streaming company, but that data is confidential so I can’t share it. In addition, I’ve done deep dives into other parts of entertainment, but sometimes I can’t find the charts I’d made, or they were on other computers. So that’s a bummer.

Caution 2: I’m limited by available data.

In many cases, I don’t have access to the database that has all the information. To really show a log-distribution, you need all the data, not just slivers. Instead, I have to rely on what I can find—the good graces of the internet—which is usually top ten, top 25 or top 50 lists, which isn’t good enough. We can still extrapolate using some logic, but if I had access to the database itself, it would all look more logarithmic.

Caution 3: I plan to update this over time.

This post has taken a lot of research, which takes time. At the same time, I promised this three weeks ago. So to manage both priorities, my goal is to post this today, then update it over time as I find more examples and/or think of more.

On to the examples.

Video

Or “filmed entertainment”. Any marriage of visual recording with audio usually performs like our logarithmic returns. But let’s start with our example from last time.

More Movies/Films

As a reminder of a perfect logarithmic distribution, here’s box office returns in 2017.Chart 2 Movies Again

In my second article, I showed how this distribution applied to multiple genres of films. Well, I recently looked at this for another genre of films. And guess what? We got the same distribution. In this case, I looked at war films.Chart 3 War Films

Source: Box Office MoJo

TV Ratings by Series

Of course, you could argue that maybe theatrical box office skews the performance of video. So let’s turn to the other primary form of video, TV. Let’s start with traditional broadcast TV. Deadline had a summary of the ratings for broadcast channels in 2017 with the top ratings by series. Unfortunately, it doesn’t look as great as I wanted:

Chart 4 Broadcast Ratings

Source: Nielsen, via Deadline

What went wrong? Well that’s “broadcast” TV. In fact, that’s broadcast “prime time” TV. People with cable (or broadcast) can watch a lot of other types of shows: daytime programming, syndicated shows and cable. Oh, all the cable.

In a future update, my goal is to expand this table. (Trust me I’ve google the internet for a while and this is the biggest hold up to me posting today.) If I had access to Nielsen, I could do make the table pretty quickly. Instead, they only provide “Top 10s” and I can only find prime time broadcast on publicly available sites. (I made this chart for work before with Nielsen data.)

So I’m not off to a great start (though trust me, if you add cable above it looks logarithmic), but I have two other TV options to show.

TV Channels Viewership

Of course, we could also look at “TV Channels” as their own distinct entities. Do we get the same type of performance? I hadn’t initially thought of this, but stumbled across ratings by network when I was looking for data in my “CBS Myths Debunked” article. Here you go:

Chart 5 TV Networks by Viewers

Source: IndieWire

TV Subscriber Fees

Thinking of channels got me to think of another way to measure the value of TV channels, by the amount cable companies have to pay in “subscriber fees”. I don’t have time to explain sub fees now, but just know they were the straw that stirred the drink for the last few decades in cable. I had some old data from 2012 listing cable sub fees and here you go:

Chart 6 - Cable Networks by SubYou could look for logarithmic distribution in “total subscribers” in cable, but you won’t find it. There is a cap on the number of households that can subscribe to a cable channel, which nears the total number of households at 100 million-ish. As a result, when cable channels hit that upper limit, they used fees to capture the extra value.

Streaming

So Netflix, Amazon, Hulu and the rest don’t share ratings data. So no charts here. But I’ve seen the data for one of the streamers, made the charts, and let me assure you this: this law absolutely applies. The most popular shows on a streaming platform are multiples bigger than the vast majority that come, go and are forgotten. If anything, given the larger sizes of the platforms, the effects of the log-distribution are more pronounced.

Speaking of size of libraries, let’s head to the largest library of video on the internet.

Youtube

Know this: if you search for information on the number of views by video, you find a lot of articles on “Gangnam Style”. Which I’m not saying to be negative, just pointing out.

Search hard enough, and I did, and I found the key insight here. This long, information article on a website called the The Art of Troubleshooting, where he used some scraping and R to pull the data on the video views. I took a screenshot of his “log-normal distribution” of video views. (In other words, he converted the logarithmic distribution into “logs” to show the normal distribution. It’s the same thing, it just looks different because the scale is in log.)

Here’s the picture and another link to his site.

Chart 7 - Youtube Log Normal

Source: Art of Troubleshooting

The insight with Youtube makes sense: “Despacito” and previously “Gangnam Style” have literally billions of views. Yet, since anyone can make a video, the vast, vast majority have 0-100 views. This effect continues with channels as well, as measured via subscribers, sort of like how I measured both by show and channel above. This article on Vox has some of the statistics showing how big the biggest stars are. For example, PewDiePie is way out front, but most people don’t have any subscribers to their channel.

Youtube is definitely winner-take-all and the distribution holds. Here’s a chart showing the top 250 channels by sub. Look at the trend:

Chart 9 - Top 250 Channels by Sub

Source: TwinWord

If we turned this into a histogram and expanded it out, we’d get our log distribution.

Social Media & The Internet

As the Youtube example shows, as the sample size grows, the effects of the power-law get amplified. Moreover, with the internet, the data is a bit easier to come across. And it makes the power-law distribution even starker.

Social Media

Let’s start with Twitter. Do the number of followers someone has follow a power law?Chart 10 Twitter Followers

Source: StatisticsBlog.com

According to this website, yep. And again this makes sense: Rinaldo has tens of millions of followers while most people are in the hundreds and bots have hardly any. This other article says that over 90% of people have less than 100 followers, which makes sense. Let’s head to Facebook. In this case, the number of friends someone has is NOT power-law, since it isn’t really consumer facing. But, the number of likes something has does follow this law:Chart 11 Facebook Followers

Source: A ScribD article via Quora

In the future, I could look at both measurements of fandom (subscribers, followers, etc) or popularity of individual posts (likes, shares, etc) on multiple other social platforms and you get the same effect each time. That’s what going viral is.

Internet

One last part of this which is how the internet started: old fashioned webpages. Do certain cites have multiples more viewers? Of course.

Chart 12 Top News Sites Statista

Source: Top News Sites via Statista

That comes from Statista, who only covered news websites. You can go to Alexa and see another list of top websites, all in the hundreds of millions of monthly visitors. Yet, according to this one website, there are 1.89 billion websites. That’s definitely power law distribution. This random paper online backs this up.

Next Time

So that’s five pages, 12 charts, and 7 or 8 different categories of entertainment (film, war films, TV shows, TV channels, Twitter, Facebook and the internet).

But I’m not done, just done for today. In my next update, I’ll try to tackle music—there are two more databases I don’t have access to—and other more unique/weird subsets like toys, comic books, sports and theme parks.