Snow Day = Twitter Day

Hypothesis: When St. Louis is canvassed with a city wide snow-day, people are much more likely to use Twitter.

One of the best parts about Infuz having a product like STL Tweets is the data analysis we get to do.

STL Tweets, for the uninitiated, is a localized Twitter discovery and aggregation engine. The amount of data STL Tweets collects and catalogues from Twitter on a daily basis is immense. We pick up all tweets that originate in or around St. Louis and all tweets about St. Louis. This means we get to see how many people are truly using the service and when.

Cut to this week.

Weather reports on Sunday suggested that Monday through Thursday(1/31 – 2/3) we may see blizzard conditions that haven’t hit the St. Louis area since 1982. Cue instant pandemonium and egg riots at your local Schnucks. While the weathermen may have been about as sharp as Kenneth Cole’s sense of humor, we did learn one thing from this whole fiasco…

If you have a snow day, you are probably on Twitter.

Data

Let’s dig into the data and look at some trends, starting with Saturday (Jan. 29) and Sunday (Jan. 30).

You can see the drop in traffic from midnight to 4am as people sleep. This is a pretty standard curve. Traffic then grows until around 8am when people begin their day and set their phones or laptops down for intervals. Next let’s look at Monday and Tuesday.

There’s a few things to note here. Monday started like a typical day, with most people going to work in spite of the treacherous forecast. 8am to 3pm tracks like a normal day, before the weather begins to deteriorate. Then the weather turned and people left work early, evidenced by the tweet level dropping from 3pm to 5pm. The real surge in tweets came at 10pm, as circled, when many more people than usual started tweeting about the freezing rain and impending blizzard.  Tuesday is when the fun really began.

Tuesday morning the curve started in the typical way, ramping up from 4am to around 8am. Looking at the right box above you can see the volume of tweets explode from 8am to 2pm, spiking at seven thousand tweets around 2pm. Notice this progression is without any lulls along the way. Typically tweet volume is up and down during the day… that’s when the workforce of St. Louis is in the office filing their TPS reports. When the boss is away… the tweeps will play. Why take breaks to work when you’re on your couch watching The Price is Right?

Findings

The raw numbers:

Entire 2010 Feb 1st, 2011
Average Daily Tweets 39,029 95,062
Average Tweets at 2pm 1,825 7,452
Average People Tweeting, Per Day 10,359 18,373
Average Tweet Per Person, Per Day 3.77
5.17

We can calculate a few things here:

  1. Twitter is more likely to be used in times of uncertainty, making it a 2-way news source
  2. People are more likely to use Twitter during snow days

Here’s a look at the full spread from Saturday through Tuesday below for a bigger picture.

Pretty stark difference. While we can all assume the boost in tweet volume was due to the snow… we can also look at hash tags for some validation. #snowpocalypse, #stlsnow, #snOMG and #snowmageddon were all used in high volumes that day.

Your Thoughts?

So were you one of the thousands in St. Louis tweeting more than normal during the #snowpocalypse? What other St. Louis trends on Twitter are you interested in learning more about?

Leave us a comment and let us know below, or just hit us on Twitter at @infuz.

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  • http://www.falkharrison.com Chris Reimer

    Great post Brad. I assumed volume would be up due to uninterrupted snow-tweeting, but it’s good to see hard numbers. It’s also amazing how the #STL hashtag gets dominated when inclement weather strikes.

  • Brad

    Don’t get me wrong… #STL was still by far the most used hash tag that day. Thanks for the comment Chris!
    -Brad (@JavaSTL)

  • http://owenj23.tumblr.com/ Brian (@owenj23)

    Great analysis, I’m terribly jealous of your database ;) It was kind of cool to see #stlrules trending on twitter Feb 1, but I had no idea what kind of surge it took to get a keyword up there.

  • Brad

    I’m not going to lie Brian… it’s a pretty wicked database. :)
    -Brad (@JavaSTL)