“And I’m like ‘Honestly, I don’t know nothing about mopeds’” -Macklemore
Mopeds are a thing. A thing that exists. A thing that has had approximately zero influence on my life. People in Europe drive mopeds, people in America drive literally anything else. But then I watched the music video of Macklemore’s & Ryan Lewis’s new song “Downtown.” The video begins with Macklemore naively purchasing a moped which he proceeds to ride around the ‘Downtown’ for the remainder of the video.
“Oh yeah mopeds, those exist” I thought, and headed to Google to see if a moped is right for me [Spoiler: It is not]. But then I wondered how many other people were similarly inspired to dive into the fabulous(?) world of mopeds.
Google, of “Don’t be Evil” fame, obviously tracks every search performed on its site and the aggregated data is available through Google Trends. Below is the Google Trends plot for the search term “moped” from 2004 - present in the United States. An interactive version of this plot can be found here.
The most prominent feature is the large spike in the summer of 2008. When the financial crisis hit people were thinking of ditching their Hummers and opting for something that gets 70 mpg. What is curious is that this was not a persistent trend, even though people were supposedly strapped for cash for the next few years of the recession. Everyone did their moped research in 2008 and decided that mopeds were not for them. Conversely, everyone bought a moped in 2008 and they all still have them and have no need to ever search for anything moped related. Anecdotally, the number of mopeds I see is still approximately none so I will choose to believe the former.
Because Google Trends only displays relative search numbers, and the 2008 spike was such a huge outlier, I chose to rerun the analysis from December 2008 until the present to achieve greater “resolution” to answer the question of interest. Explicitly, how has “Downtown” affected searches for mopeds?
Because searches for mopeds are cyclical, we can average these to get an idea of how Macklemore’s song has deviated interest in mopeds. Here is a plot of the average number of relative moped searches by month (bold). Each individual year is also shown, with 2015 highlighted in red.
As you can see, 2015 has been a bit below average, but there was a small increase at the end of the month in August, which is when “Downtown” was released (indicated as a dotted line). Then in September, instead of dramatically plunging as Fall approaches, the number of searches for mopeds stayed relatively stable. September’s search traffic scored a 74, almost 17 points higher than the average for this time of year, and statistically different than the mean. More people than usual are actually looking for mopeds because of this ridiculous song.
There is no way to know if this increase in traffic will actually lead to more mopeds on the streets, especially when Winter is Coming. Nevertheless there appears to be a causal relationship between this song and moped searches. As “Downtown” continues to rise in the BillBoard Top 100 (it has only been on there since the September third and is currently sitting at number 16 at the time of writing) the last question we have to ask ourselves is: How much is Big Moped paying Macklemore?
Click Below to Watch the “Downtown” Music Video.
I know what you are all thinking: which state has the most beautiful college-aged women? A question for the ages to be sure, one that if I ask again in a few years would probably end with me in jail. Total Frat Move has been faithfully performing the Lord’s work and compiling a database answering that very question.
TFM’s ‘Instagram Babe of the Day’ showcases one Instagram account featuring a woman wearing clothes that her father must...just...not know about. Using the tools at Kimono Labs I assembled a list of 299 IBoDs and sorted them by state. Here are the results in a fraternity-approved-salmon colored map:
Florida is the winner and it is not even close at 67 ‘Babes’ of the 299, or 22%. California is the next closest at 49 followed by Arizona at 38, Texas at 21 and then Virginia and New York with 8 and 7 respectively. In fact together the top 3 states beat out the bottom 48 (including DC) combined. The entire country of Australia had 1 which puts it ahead of the six states with zero. America’s friendly neighbor to the North, Canada, came in at 4 beating out 34 states.
Clearly not all states are equally gifted. Warmer states seem to be dominating and the upper portion of the Midwest is just a deserted wasteland. But Wyoming only has 6 people per square mile. I didn’t expect there to be bronze bombshells patrolling the streets of Cheyenne. But even adjusting for the number of female college students per state does not even the playing field. Here is a graph of the total number of IBoDs plotted against female college students by state (data are in thousands, from 2008; available at the US Census. Thanks Obama).
Florida and Arizona are really just doing a great job. Keep it up gals. Texas and especially New York are under-performing their potential. Both have fewer TFM ‘Babes’ than would be expected based on their student population. Hawaii, with its low student population, actually has the highest rate of IBoDs. Around 1 in every 8500 college girls is on TFM. Florida’s rate is the only close competition at 1:9000 followed by a distant Arizona.
Babes of the Day is only one metric though. Is it really accurate in predicting the most beautiful states? I looked up some other rankings and chose two (the first two that came up on Google). The first was from the internet’s bastion of journalism, Buzzfeed, and the other was from Comcast Xfinity (even they have lists?). Both used a combination of arbitrary numbers to reach their equally dubious conclusions about the most attractive states. Here are the top 5 for each in descending order. (I switched back to using total number of IBoDs for this one because it gives a better list. Rigor is not the goal of this analysis)
No surprise, California shows up on each list. We also see Florida and Virginia show up on one of the other lists. The other two lists have Hawaii which would have been there if we had taken into account total number of college girls. So overall 3 of our top 5 ended up on the other lists which gives us a 60%. Plus 10% extra credit for Hawaii almost being on there gives us 70%. And C’s get degrees.
There is no way to differentiate between correlation and causation. Either warm weather attracts beautiful women, makes women beautiful or coerces them to send their names to TFMintern@grandex.co. Who cares though? I’m not complaining.
How old are you? How old does your computer think you are? That is the question Corom Thompson and Santosh Balasubramanian over at Microsoft have been thinking about. With Big Data it probably is not too tough for a computer to crunch the websites you visit and the purchases you make online to spit out a reasonable guess for your age. That’s how targeted advertising works. But what if computers only had pictures of you? Behold how-old.net. Just like that carnival “game,” can a computer guess your age by just how you look?
Um…I guess not. But this was only one trial, so I decided to try again…seventy-five more times. All with pictures of myself. This quickly devolved into quite a narcissistic project. This involved delving into the photos on my Facebook profile which proved to be both a hilarious and horrific endeavor. After shamefully mining my own photographs I ran a simple regression to get a rough idea of how the algorithm was doing.
Just for fun I decided to break the images into pictures where I was wearing glasses and pictures where I was not. If the algorithm is reading facial features glasses could be affecting the results. This divided the images almost exactly in half.