The image above is a map
taken from a New York Times article on N.B.A. fan base. Each color represents a team and the extent
of their fan base, shown in varying shades depending on how dense the
location’s devotion is to one team (Giratikanon et al, 2014). As with most of the newspaper’s maps, it is
intriguing to look at, but a close inspection reveals some problems.
The
title is good; it draws the reader in by asking a question, then states what
the map is about. There is no legend
however, so the reader must infer that each color on the map represents a
specific team. This can be troublesome
because it isn’t immediately obvious that the Lakers are “America’s Team”,
which is shown in shades of purple across most of the country. (When I first saw the map, I thought the
purple and gray areas didn’t have any strong fan base.) Another problem is the source information isn’t
displayed on the map; the article needs to be read to find it. Also, the font is a little hard to read
because of the color; oddly the Nets are by far the clearest to read, having a
black font on a white background. To
make the map more legible, I would have chosen black for all the teams and not
used it as a color on the map.
The biggest problem with the map is its data source. The writers of the article claim it was
calculated by analyzing Facebook likes per zip code. “We then applied an algorithm to deal with
statistical noisiness and to fill in gaps where data was missing” (Giratikanon
et al, 2014). It isn’t clear what this
means, and the idea of reporters modifying statistics isn’t a good one. They should have gotten data from a more
reputable source and been more transparent about the data collection
method. At least they acknowledged it is
an imperfect method in the article, but then they justified it by saying “Facebook
likes show broadly similar patterns as polls do” (Giratikanon et al,
2014). Based on how consistently the map
matches up with each team’s host city, the data might seem accurate, but there
is no statistical information present in the article, nor is there a link to
any. The reader can’t tell if the map is
showing solid data, or if it was made up.
It also fails to meet cartography standards because the source for the
data cannot be found on the map itself.
Another issue is that the map does not include the only
Canadian team in the N.B.A: the Toronto Raptors. This omission makes the map incomplete. Thus, I would have included southern Ontario
on the map, but not the rest of Canada because it is so big. Including Canada on the map would have been
it less aesthetically pleasing, due to the enormous amount of land that would
supposedly favor the Raptors or Lakers. My
addition would give a fair representation to the Raptors and still keep the map
in balance.
There is a risk of ecological fallacy on this map, where
the reader might assume that just because a city hosts a team, the region
surrounding it will have a high fan base.
But if we look closely at the map, we notice several cities have
relatively low fan bases compared to the surrounding region (Atlanta Hawks,
Washington Wizards, Charlotte Bobcats).
To guide the reader away from that assumption, I would have put more
text in rural regions where the Lakers, Heat, or Spurs are more favored. Being that the map was made in 2014, when the
Heat and Spurs were in the N.B.A. finals, it is no surprise to see them as the
favorites in much of the south-east. To
underline the importance of this, I would add a caption stating that this is a
historical snapshot of the N.B.A. and not a current one.
As for color, most of those on the map match the team
logos and jerseys, making them familiar to fans. The most glaring exception is the Miami Heat,
which should be red. I can’t imagine why
they decided to use black, unless they were trying to match them up with the
Spurs, who were also in the finals that year.
Also, I would have used yellow to describe the Pacers and Warriors, since
that is their true color and purple and blue are already in abundance on the
map. The resulting higher variation in
color would help to discern the boundaries between fan bases more.
I think the message of the map is straight forward and
there is no underlying one intended by the writers. Perhaps an unintended message is that teams
in the finals deserve more attention and that is why we see them more
represented on the map. Logically they
would get more attention from Facebook’s algorithms, as the finals are a huge
public event, and the algorithm boosts the popularity of newsworthy items. More likes for these teams in rural areas
seem inevitable, so eliminating them from the data in appropriate places might
have made the map more accurate.
Regardless, I found it to be a fun and interesting look at where fans
gravitate around the country.
Giratikanon, Tom, Katz, Josh, Leonhardt, David, Quealy, Kevin. 2014, October 19. Which Team Do You Cheer For? A N.B.A. Fan Map. The New York Times. https://www.nytimes.com/interactive/2014/05/12/upshot/12-upshot-nba-basketball.html
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