Six Degrees of Separation, Twitter Style

Six Degrees of Separation, Twitter Style

April 2010
Alex Cheng, Sysomos Inc.

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Over the past year, we've spent a lot of time exploring Twitter, and one of the things we've been curious about is how connected people are to each other within the Twitter network.

So, we sliced and diced more than 5.2 billion Twitter friendships (the number of friend and follower relationships) to investigate the connectivity of the Twitter network. We discovered that Twitter is, in many, ways a network with only five degrees of separation. This means that nearly everyone on Twitter is just five steps away from each other. We describe this separation between two people as "friendship distance".

Here are our major findings:

  • The most common friendship distance is five steps. (The average distance is 4.67 steps)
  • The second most common friendship distance is four steps.
  • On average, about 50% of people on Twitter are only four steps away from each other, while nearly everyone is five steps away.
  • After visiting an average of 3.32 people within the friend network, Twitter users can expect to find one of their followers!

The "Six Degrees of Separation" theory was created by Hungarian author, Frigyes Karinthy, in the early 20th century. In the 1960s, U.S. social psychologist Stanley Milgram did a series of "small-world experiments" to estimate the average distance between individuals within a social network.

In his small world experiments, Milgram randomly selected 240 people living in U.S. cities. These people were sent letters that included information about another person (aka the target person), who they likely didn't know. The 240 people were asked to forward the letter to a friend, who they thought might know the target person. When a letter finally reached the target person, Milgram counted how many times it had been forwarded to determine the number of "steps" needed to reach the target person. Of the 60 letters that made it to the target person, the average number of steps was 5.5 to 6, which provided evidence for six degrees of separation.

The graphics below provide examples of friendship separation. Each circle represents a user on Twitter. The intersection between two circles represents a friend relationship.

Twitter Network Friendship

Twitter Friendship Distance

On average, Twitter users have five degrees of separation between each other - meaning nearly everyone within Twitter is only five steps away. Of all friendship distances, five steps is the most common (41%), while a friendship distance of four steps is the second-most common (37%).

Here is a pie chart that shows the different Twitter friendship distances:

Twitter Friendship Distance

The table below shows the number of steps between Twitters users, and the percentage of total Twitter friendships within a specific number of steps.

Twitter Friendship Distance Table

Reach-ability of the Twitter network

One way to measure the connectedness of Twitter is by looking at the percentage of Twitter users that can be touched by reaching out a certain distance. Using the Twitter network graph, we discovered that, on average, a Twitter user will encounter 83% of all other Twitter users by visiting everyone's friends up to a distance of five steps. If the user visits all friends of friends up to six steps, 96% of all Twitter users will be covered. This means, the Twitter network has good social connectivity, and that, in theory, a re-tweet (RT) does not have to propagate that much to reach a potentially large number of people!

Reach-ability of the Twitter network

The table below shows the reach-ability of the Twitter network by the number of steps. The more you reach out on Twitter; the percentage of all Twitters users discovered grows exponentially.

Reach-ability of the Twitter network table

Local-ness of the Twitter network

How far does a Twitter user have to roam before they meet a follower of their own? Apparently, not that far. We discovered it only takes 3.32 steps to find someone who is following you (with a standard deviation of 1.25 friendship distances). This means, if you trace your friends, and their friends and so on, in 3.32 steps on average you will discover a follower of your own. This means, there are many small, circular connections on Twitter.

Local-ness of the Twitter network

Methodology

Sysomos created the Twitter network by connecting users with their friends. These twitter users were extracted from the large database of conversations we use for our social media monitoring and analytics offerings MAP and Heartbeat. We examined 5.2 billion friendship connections on the Twitter network. Based on our analysis of this network, we discovered how connected the users are to each other.



About Sysomos

Sysomos | Business Intelligence for Social Media, Monitoring and Analytics

Sysomos is redefining social media monitoring and analytics by providing corporations, marketers, public relations agencies and advertisers with the intelligence and insight needed to make smarter business and strategic decisions. The Sysomos platform provides instant and unlimited access to all social media conversations to see what's happening, why it's happening, and who's driving the conversations. Sysomos.com.

Sysomos' products include

MAP - Social Media Analytics Platform MAP: A feature-rich service that offers customers the ability to analyze and understand social media conversations. MAP delivers insight and intelligence about the major conversations, why they're happening and who's driving them. You can make unlimited queries on any topic to get real-time results, collaborate, and generate detailed reports for clients.

Heartbeat - Social Media Monitoring Heartbeat: A cost-effective, real-time monitoring and measurement tool that provides constantly updated snapshots of social media conversations delivered using a variety of user-friendly and intuitive graphics. Heartbeat organizes conversations, manage workflow, facilitate collaboration, and provide ways to engage with key influencers. Feedback

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Sysomos has collected a comprehensive collection of data from Twitter user profiles and updates. We will be publishing our analysis of this ever-changing and growing data on a regular basis. To leave comments (including the kind of information you would like to see in future) about this report, visit our blog.