Blog Index
The journal that this archive was targeting has been deleted. Please update your configuration.
Navigation
« A Simplified Football Prediction Model | Main | Possession Analysis: A Closer Look »
Thursday
Jul192012

Visualizing Twitter Data

Inspired from this post on plotting the frequency of Twitter hashtags over time, I was interested in trying to apply this to soccer some way. While not the most technical analysis, I thought it would be interesting to use this tool to analyze transfer rumors.

To summarize the process quickly, there is a package in R (open source statistical software) called TwitteR which allows you to pull Twitter data. It's actually a fairly easy process, especially if you follow the tutorial in the link at the beginning of this post.

As most Twitter users know there is a seemingly unlimited number of transfer rumors circulating Twitter. These range from being fairly plausible to pretty ridiculous ("Ronaldo to the Philadelphia Union???).  As a Manchester City supporter, I was curious at looking at a few popular transfer rumors related to City.

Robin van Persie to Manchester City:

Yes, this is definitely a rumor, and yes, it is probably not going to happen. But I was still curious. Below is a plot of the frequency of the number of tweets that include "Robin van Persie" and "Manchester City". Of course, this is an imperfect method, but it still gives us an idea of what is going on in the Twitter transfer rumor world.

To explain, the graph below measures the number of tweets described above at a 2 hour interval for the past week. This means the height of every line gives us the number of tweets referencing RVP and City in that 2 hour interval.

 

Carlos Tevez to AC Milan:

After Tevez's past season with the club, there are obviously transfer rumors concerning Tevez all over the place. Because of this, it was hard not to want to look at the data on Tevez. I picked AC Milan because it seemed like the club he had the highest likelihood of going to. Like above, I searched for tweets that included "Carlos Tevez" and "AC Milan". The frequency of these tweets, in 2 hour intervals, is plotted below.

You can try to analyze these graphs to find some meaning, but they are more just a fun exercise than anything else. The TwitteR package lets you do other cool things, like plot the frequency of Twitter mentions for a user. I did this for another site I write for, EPL Index. They tend to get a lot more mentions than @SoccerStatistic does, so I thought it would be more interesting to plot the frequency of @EPLIndex mentions. Again, the intervals are every 2 hours.

Like I said before, this analysis is not very insightful or ground-breaking, but still pretty cool nonetheless. The possibilities for future analysis like this are almost endless, so if people have good ideas of Twitter data to visualize, I'd love to hear them.

References (7)

References allow you to track sources for this article, as well as articles that were written in response to this article.
  • Response
    Response: this contact form
    Amazing page, Preserve the wonderful job. Thanks a ton.
  • Response
    Response: fivefinger shoes
    One by one, they either sold out to the big boys, or they simply went out of business.
  • Response
    Response: dvnf
    SoccerStatistically - Blog - Visualizing Twitter Data
  • Response
    Response: fifa 14
  • Response
    SoccerStatistically - Blog - Visualizing Twitter Data
  • Response
    SoccerStatistically - Blog - Visualizing Twitter Data
  • Response
    SoccerStatistically - Blog - Visualizing Twitter Data

Reader Comments (1)

Don't worry about trying Twitter, when I first started using it. The key to using Twitter is finding a way to use it that works for you.
Twitter , twitter follower, Is Popular version in this moment, comments will be write for this position.

PostPost a New Comment

Enter your information below to add a new comment.

My response is on my own website »
Author Email (optional):
Author URL (optional):
Post:
 
Some HTML allowed: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <code> <em> <i> <strike> <strong>