Space Shuttle Endeavour, on the STS-123 mission, lights up Launch Pad 39A and the night sky. Liftoff was on time at 2:28 a.m. (EDT) March 11. The crew will make a record-breaking 16-day mission to the International Space Station and deliver the first section of the Japan Aerospace Exploration Agency's Kibo laboratory and the Canadian Space Agency's two-armed robotic system, Dextre. (NASA photo/Jim Grossmann)
Space Shuttle Endeavour, on the STS-123 mission, lights up Launch Pad 39A and the night sky. Liftoff was on time at 2:28 a.m. (EDT) March 11. The crew will make a record-breaking 16-day mission to the International Space Station and deliver the first section of the Japan Aerospace Exploration Agency’s Kibo laboratory and the Canadian Space Agency’s two-armed robotic system, Dextre. (NASA photo/Jim Grossmann)

For my twitter API project I decided to collect data from NASA and SpaceX’s twitter pages. My original goal was to find out about a single event that occurred the week of 3/23-3/30 through the frequency of specific words in NASA’s tweets. This effort was in no way shape or form wasted. While I did have a little trouble, I was still able to dissect over 30,000 tweets for common words and trends. About 200 words proved useful to my research. One of the tricks was to disregard any false words that registered with abnormally high counters. For example, Elon Musk had over 4,000,000 tweets, President Obama had over 1,000,000, or some random looking numbers 34kjlkj098393kj9 that represent some internet mumbo jumbo. While the President and Elon Musk are very important figures, they were not surprising factors for my research. They were merely bonus data that was already a given. However, I did learn that not all gibberish numbers should be written off for not. Because my initial research delved into one of Nasa’s ISS flyover’s which I only discovered by tracing this image’s tag(zhq9zqp94u) back to it’s source. Then I pieced together the rest of the event by finding relevant keywords that had a high word frequency count. Which eventually lead me to an even better set of data from twitter.

My second set of data revolved around the Falcon 9 mission which was lead by the private company SpaceX. My trail begun by researching NASA, but upon my research I realized that the ISS was going to have another supply mission rather soon. My timing couldn’t have been perfect. These events were only a couple weeks apart and well within the projects time limit. I found it incredibly fascinating to see what NASA’s followers were saying so I decided to do the same for SpaceX and play around with the data. Not, that the results were surprising. Elon Musk’s companies pretty much advertise for themselves. I wrote about it here at my website.

Twitter API