Non-randomness in Forbes' Celebrity 100 ranking

Some time ago I blogged about The mysterious rankings in Forbes' Celebrity 100. I noted at the time that "There are some other things that we can learn from an analysis of the Celebrity 100 list, but they have nothing to do with networks, so I will not cover them here." I will, however, cover these things now.

Each year since 1999 Forbes magazine has produced a list called the Celebrity 100, which purports "to list the 100 most powerful celebrities of the year" within the USA. The list is based on entertainment-related earnings plus media visibility (exposure in print, television, radio, and online). The 2012 list generated plenty of negative comments around the web, and my network analysis of the data showed that there is little apparent mathematical logic to some of the rankings.

However, the data do also reveal interesting patterns about the perception of celebrity in the media, provided that we accept the quality of Forbes' data (even if we find fault with what Forbes did with those data). In the graphs below I have simply used the information provided by Forbes in order to take a look at some of the features that Forbes did not comment upon.

The first graph plots the celebrity ranking by sex and "profession". Each dot represents one celebrity, with one black and one blue dot per celebrity representing their sex and profession, respectively. They are arranged in the Celebrity 100 order, left to right. You will note that the data are not randomly distributed among the groups.

The graph shows that one third of the celebrities are female, and they dominate the top 10 and the bottom 30. So, in order to get a high ranking it is best to be female but that after that it becomes a handicap.

The other groupings are based on the Forbes description of each celebrity's principal claim to fame. Clearly, in terms of celebrity status: being a musician is better than being an athlete, which is better than being an actor, which is better than being an actress. Being a TV or radio personality is not bad, either. Note that this explains the bi-modal distribution of females: the music females are in the top 10 while the acting females are in the bottom 30.

For the rest, if you are a male, then being a producer/director is marginally better than being an author, which is marginally better than being a comedian. If you are female, then  being a model is much worse than being a singer or an actress. Being an entrepreneur works only if you are Donald Trump.

The second graph compares each celebrity's money ranking (based on an estimate of their earnings) with their overall ranking. This is an attempt to see who is financially benefitting from their celebrity status (or vice versa). Once again, each dot represents one celebrity, with the location reflecting their Celebrity 100 rank (decreasing to the right, horizontally) and their earnings (decreasing towards the top, vertically). The two lines on the graph show that for most celebrities (those between the lines) their financial status closely follows their celebrity status.

However, for those at the top-left of the graph their celebrity standing is greater than they are being paid. (They are ranked in the top 30 on overall celebrity status but are not in the top 25 money earners.) This means that their manager is "not getting them what they are worth". These people are, from top to bottom on the graph:

Jennifer Aniston Kim Kardashian Angelina Jolie Brad Pitt Adele Adkins Beyoncé Knowles Katy Perry Jennifer Lopez Stefani Germanotta (Lady Gaga) Rihanna Fenty Justin Bieber

actress television personality actress actor singer singer singer actress singer singer singer

You will note that there are nine females but only two males in this list. Note, also, the number of singers in the list, indicating that being a singer will get you more celebrity than money.

For those at the bottom-right of the graph their celebrity standing is less than their monetary worth. (They are in the top 25 money earners but are not ranked in the top 25 on overall celebrity status.) This means that their publicity agent is not doing their job (or not being asked to!). These people are, from right to left on the graph:

Mark Burnett Kenny Chesney Toby Keith Jerry Bruckheimer James Patterson George Lucas Michael Bay Howard Stern

television producer   country music singer   country music singer   film and television producer   author   film director and producer   film director and producer   radio personality

These people are all male, so these males have more money than celebrity. Most of these men do not work directly in the public spotlight, or they prefer country music to pop music.

One can perform a similar analysis to compare the celebrities' TV/Radio rank with their Press rank. This produces a very similar graph. It turns out that the people whose TV/Radio rank is poor compared to their Press rank are mostly athletes (David Beckham, Roger Federer, Lionel Messi, Li Na, Cristiano Ronaldo, Maria Sharapova), along with one model (Kate Moss) and one producer/director (Steven Spielberg). The thirteen people whose Press rank is poor compared to their TV/Radio rank are almost all TV/Radio "personalities", as expected.

I am sure that there is more to be found in this dataset, if anyone cares to look.

The mysterious rankings in Forbes' Celebrity 100

Every year since 1999 Forbes magazine has produced a list called the Celebrity 100, which purports "to list the 100 most powerful celebrities of the year" within the USA. The list is based on entertainment-related earnings plus media visibility (exposure in print, television, radio, and online). The current list was released in May 2012 (see The World's Most Powerful Celebrities).

The 2012 list generated plenty of negative comments around the web, typified by this one from the Huffington Post: "Looking at the list and the various artists' rankings in the five categories used to determine their placement, there's a sense that the actual positions are more arbitrary than usual. For example, Jennifer Lopez is #1 despite not ranking inside the top 10 in any of the categories (and is as low as #30 in money, #22 in press rank and #19 in social), while both Lady Gaga [Stefani Germanotta] and Justin Bieber earned top 10 placements in all of them except the Money Rank, the top tier of which is dominated by multimedia moguls like Oprah Winfrey".

Forbes' Celebrity 100, top three.

Forbes lists the five categories (designed to measure "earnings and fame") as follows, along with the data sources they used:

• Money Rank — talk to industry insiders to come up with an estimate of earnings
• TV / Radio Rank — use Lexis / Nexis to find out how many times each star was mentioned on television and on the radio
• Press Rank — print media mentions come from Factiva
• Web Rank — measured using Google blogs
• Social Rank — count of Twitter followers and Facebook fans.

Each celebrity is ranked within each of these categories separately, and then: "all of the data is processed through an algorithm that creates our power ranking."

The following criticism appears among the comments on the Forbes blog page: "I’m not sure what your algorithm is based on, but it’s clearly not the rankings you provided, given that Beiber and GaGa tie or outrank J-Lo in every category, and Oprah beats her in all but one category and made more than three times as much $. Seems odd ..." Indeed, both Rihanna Fenty and Beyoncé Knowles also out-ranked Lopez in four of the five categories, and yet Beyoncé was ranked only 16th and Rihanna 4th.

In reply to the criticisms, Dorothy Pomerantz (the Forbes editor in charge of the list), noted: "The thing that doesn't show up on the celebrity profiles is magazine covers, and it counts for a lot ... We comb through dozens of magazines from the past 12 months to count how many times each star appeared on covers." This comment generated the response: "to leave magazine covers out when it supposingly 'counts for a lot' is crazy, and nonetheless it still seems weird Lopez could come out on top."

To quantify whether the rankings are indeed 'crazy' or not, we can use a network as a useful means of exploratory data analysis. As usual, I have used the manhattan distance and a neighbor-net network, but this time I have applied them to the rankings for each of the five celebrity-status categories, as listed by Forbes. If the final ranking in the overall Celebrity 100 list really is based on a pooling of the rankings for the five individual categories, then there should be a simple pattern in the resulting network, with similarly ranked celebrities appearing near each other in the graph. That is, people who are closely connected in the network are similar to each other based on their category rankings, and those who are further apart are progressively more different from each other.

The neighbor-net graph of the people in the Forbes Celebrity 100,
labelled according to their ranking.

However, this is blatantly not the case. To highlight this fact, I have coloured the top ten celebrities in red and the bottom ten in purple on the network. While it is true that the red numbers are down at the bottom of the graph and the purple ones are at the top, thus forming a pattern of sorts, the different colours are clearly not clustered together (the red form two separate groups rather than one, and so do the purple). So, it is not just the Lopez ranking that is screwy — a lot of the ranks appear to be fairly arbitrary.

If we look at some specific examples, the people at rank 16 (Beyoncé Knowles) and rank 24 (Adele Adkins) are clustered in the network with those people with ranks 1-8, while the people with ranks 9 and 10 are far away from 1-8. This means that, given their performance on the individual criteria, Beyoncé and Adele should be in the top ten on the Celebrity 100 list, and yet Forbes has them ranked as 16 and 24. Why? Surely their magazine-cover performance cannot have affected them that severely.

Alternatively, neither Britney Spears (ranked 6) nor Tom Cruise (ranked 9) made it into the top ten on any category, and yet the are both ranked in there, whereas everyone else ranked inside the top 16 made the top ten in at least one category.

As other examples, we can note that rank 48 is near ranks 9 and 10 in the network while rank 49 is near ranks 98 and 99; and rank 83 is next to rank 22 (near the bottom of the graph) while 26 is next to 81 (near the top)!

The Forbes so-called 'algorithm' must be a sight to behold, because it produces an outcome that is not quite random but nevertheless does a very creditable imitation of it. I think that we can safely say that there is more than 'magazine covers' involved in these ranking discrepancies.

A much more reasonable top dozen, based on the graph, would be the people ranked 1–8, 11, 15, 16 and 24. These are, in alphabetical order:

• Adele Adkins
• Justin Bieber
• Rihanna Fenty
• Stefani Germanotta
• LeBron James
• Kim Kardashian
• Beyoncé Knowles
• Jennifer Lopez
• Katy Perry
• Britney Spears
• Taylor Swift
• Oprah Winfrey

The exact rank order of these people would, presumably, be determined by the number of magazine covers on which they have appeared.

There are some other things that we can learn from an analysis of the Celebrity 100 list, but they have nothing to do with networks, so I will not cover them here. (I have now covered them in this later blog post: Non-randomness in Forbes' Celebrity 100 ranking.)