Alexa alarm clock goes off, I deactivate it with my voice
I check my phone of my emails, moving some to the trash, flagging the important ones
I go downstairs to the dining hall for breakfast swiping my MIT ID
In the cafeteria line, I check instagram and snapchat
Read news on the bloomberg app
Buy lunch at Clover
Check my coinbase account and sell some of my bitcoin
Buy a coffee at Starbucks
Send some funny gifs to my friends through facebook messenger
Answer questions on the MITx platform
Series of google searches on linear algebra topics
Write some emails
Go to dinner at McCormick Dining hall
Read a couple articles on Medium.com
Download next week’s psets off Stellar
Watch the olympics on xfinity.com
Ask Alexa about tomorrow’s weather and set an alarm to wake up tomorrow
People often feel a connection to their community/town/region, manifesting itself most ostensibly in the support of a sports team. While the borders between cities, counties, and states are often arbitrary, social media lets us see how our allegiances truly lie around this country. This New York Times visualization shows which MLB teams have the greatest fraction of Facebook likes within a zip code. Aggregating the data literally paints an interesting picture, in some cases redrawing borderlines around the nation. The creators of this visualization overlay team colors onto the map, creating a heat map of allegiance to each team.
Created for the statistically-minded sports fan, this visualization attempts to show where each team has developed a following. The authors focus on the boundaries between rivals or metro areas, to support the hunches of baseball fans about where one team’s turf ends and another begins. Diving into the data, we can see how certain teams, such as the New York Yankees have expansive influence well into Connecticut, but surprisingly also around Las Vegas, North Carolina, and Montana. Oppositely, teams like the Oakland Athletics or New York Mets are unable to capture the zip code around their own stadium.
This is an effective visualization because it elaborates on an important question: what are the distinct regions of the US. The sample size for the data is large and the results both plausible and surprising. The graphic is relatively easy to read and guides the viewer to some of the interesting contrasts, like between the LA Angels and Dodgers or the Cleveland Indians and Cincinnati Reds. The flaw with this visualization is that it hides information that I would like to see. For example, the color shading doesn’t show anything about which team is 2nd most popular. While the percentage of supports for each team is provoking, it would be helpful to see how many supporters are recorded for each team, or at least the sample size for each zip code.
This visualization is aesthetically attractive, surprising, and also plausible enough to be credible. To take it to the next level I want to see more information overlaid about the 2nd place teams, how other sports compare, and how other measures of cultural influence interact with fan heat map for America’s favorite pastime.