Who Won Twitter Gold? Social Standouts at Sochi

With last night’s Closing Ceremonies complete, the Sochi Winter Games have come to a close. It was a few great weeks of sledding, sliding, skiing, skating, and of course, social media. As the athletes pack their bags and Bob Costas finally finds out what on earth is going on with his eye, let’s take a final look at Olympic social data and find out who won social (and why), how athletes grew together, and why figure skaters aren’t having ANY of this up in here.

Let's kick it off by looking at the athletes that grew their Twitter following the most during the Games. Was it gold that brings followers...or something else? The following headline will probably give that away.

What Grows More Twitter Followers Than Olympic Glory? A Good Story.

The average athlete at the games built their follower base by around 140%, an impressive amount for just a few week’s time. And athletes winning individual gold medals received, on average, a bump of around 180%. But the athletes with the most aggressive follower growth weren’t necessarily the ones winning gold, they were the ones with the more popular story-lines of the games.

Here are athletes that built the largest % growth of Twitter followers during the Winter Games:

#1: Kate Hansen

  • Growth: 3,474%
  • Pre-Games: 649 followers
  • Post-Games: 23,200 followers
  • Medals: 0
  • Other reasons for growth: She went viral as the “dancing luger”, and participated in the “wolf in the hallway” prank with Jimmy Kimmel. Much respect given.

#2: 3_SDL (joint account for three Dufour-Lapointe sisters)

  • Growth: 1,767%
  • Pre-Games: 1,226 followers
  • Post-Games: 22,900 followers
  • Medals: 2 (between two of them)
  • Other reasons for growth: The iconic picture of the two sisters holding hands while receiving their medals was a defining moment from the Winter Games.

#3: Tucker West

  • Growth: 1,579%
  • Pre-Games: 386 followers
  • Post-Games: 6,483 followers
  • Medals: 0
  • Other reasons for growth: His father informed the world that Tucker was “very single" on national TV. Nice one, Dad.

#4: Noelle Pikus Pace

  • Growth: 1,141%
  • Pre-Games: 1,321 followers
  • Post-Games: 16,400 followers
  • Medals: 1 Silver
  • Other reasons for growth: Discussed overcoming personal struggles in an interview with Meredith Viera

So as you can see - gold doesn't always bring Twitter success. When athletes find ways to connect with the general public, and aren't afraid to show a personal sides of themselves, they can attract a good following of people interested to hear what they have to say well beyond the Winter Games.

Now let's move on to a big-picture view of how Sochi impacted connections between athletes. I modestly call it...

The New Olympic Social World Order

I mined the connections of almost 500 athletes on Twitter to find connections with other athletes and find patterns across countries and sports. I did this twice - a few days before the Opening Ceremonies and a few days before the Closing Ceremonies. No, not because I'm a glutton for punishment - what I wanted to see was the growth of these connections during the Winter Games, and having data from two points in time is the only way to achieve this. Do sports bring individuals and countries together with more social media connections? Did this year's Winter Games make the world a more shiny, happy place?

Let’s find out.


Winter Games Athletes and Major Subnetworks, Post-Games

During the course of the Winter Games, total Twitter connections between Sochi athletes grew by over 20%. And not only did more people connect, they connected in a way that changed the subnetworks between all of these athletes. Here’s just a few examples of some network changes that occurred:

  • Connections grew at a higher rate within countries vs across countries. While almost all groups saw increased connections between them, growth within countries like the USA (22% growth within it's own network) and Canada (27% growth within it's own network) outpaced connections within sport groups and across borders.
  • Speed Skaters, which before the Olympics were clustered in their own group, now belong to a number of other groups including the Canadian cluster and the USA Sled Sports cluster.
  • Norway’s Mens Hockey team, which before the Olympics was off in it’s own little group, created enough connections to Sweden’s Hockey team to form a two-headed Scandanavian social hockey monster.
  • USA Curling added enough new connections amongst themselvers to form their own small cluster (you can see it as the little green blob between the USA Sled Sports and Hockey), where a few weeks ago they were grouped with the large Canadian cluster.
  • Who's that green dot in the middle of Canada (red)? It's Shaun White, who gets classified correctly by the algorithm as a snowboarder, but is connected to by such a variety of different athletes that he gets positioned in the middle of the network.

Canada Goes Cross-Country

Connections within the sub-network of Canadian athletes grew by over 27%, adding over 660 social connections between Canadian athletes during the Winter Games.

You can see how tightly clustered all of the groups are in the below diagram, but there was a new group that broke out during the games.


Canadian Winter Games Athletes and Their Subnetworks, Post-Games

For Canada, it was the Cross-Country and Biathlon athletes that connected enough to form their own subgroup. This doesn’t mean they didn’t connect to any other athletes as well, just that there were enough connections formed for the algorithm to recognize them as their own group (which it could not do before the Winter Games.)

Other countries/region notes:

  • Connections within the US athletes grew by 22%
  • Connections between Scandinavian countries grew by 12.5%
  • Connections between Germany and France grew 9%

Women’s Hockey Remains Team-Centric

As I examined in a previous post, the Women’s Hockey athletes were the most divided by country of any sport I examined on Twitter. So what did a few weeks in the Sochi sun do for international relations? Not much.

Women’s Hockey continued its reign as the most densely sub-networked sport by country. Even after two weeks in the Olympic Village, teams are still clustered by themselves, with minimal connections between teams vs other sports. Connections within Women’s Hockey grew by less than 4%, way under the numbers seen within other sports, countries, and overall.

What’s Up With Figure Skating, You Guys?

As you may have heard during the games, all may not be rosy inside the world of figure skating. When checking the data, Twitter connections between figure skaters actually decreased during the Sochi Games.

That’s right, not only did they not increase connections, a few figure skaters actually unfollowed other skaters during the Games. Given the trends with the other sports and overall increased connections between athletes at the Sochi Games, the figure skating subnetwork should have created 60 new connections within their community during the Olympics. They ended up with two Twitter connections less than they started with. That's cold. Just cold.

What Did We Learn?

The Olympic Games and social networks have a few things in common: they both help connect over long distances, and both bring groups closer together. As the world becomes more connected, more data is created with every bridge. We can’t assume every connection that happens in person will be represented 1-to-1 on social networks, but the patterns we see reflect events, patterns, and trends that mirror events happening on the ground.

Analyzing events through a social lens helps to show the power, reach, and volume of social data. Some insights validate trends that have already been identified, others can uncover new insights not seen before. But to be at the top of your game, you shouldn't wait for every four years to jump into social - you should be in there every day.

Chris Kerns's picture

Chris Kerns

Chris Kerns has spent more than a decade defining digital strategy and is at the forefront of finding insights from digital data. He currently leads Analytics and Research at Spredfast. His research has appeared in The New York Times, Forbes, USA Today and AdWeek, among other publications.