Twitter Networks are like Airline Hub Maps: NPR Morning Edition story featuring study by @qaramazov @gruzd @barrywellman

Recently at study that we completed in our lab “Geography of Twitter Networks.”, with my collaborator Dr. Barry Wellman and Dr. Yuri Takhteyev was featured on NPR Morning Edition.  In this interview with Shankar Vedantam, one of my co-authors, Dr. Barry Wellman discussed some of the surprising findings from our new Twitter study.

One of the promises of Twitter is that it rendered distance and place irrelevant, turning the world into a quaint little village. However, our analysis of twitter shows that almost two fifths of Twitter ties (39 percent) are local; demonstrating that distance still acts as a powerful constraint on the formation of social ties. And for your non-local, out of town ties, you are more likely to be connected to somebody living in another city that is already connected by a commercial flight (e.g., Toronto – Los Angeles, not Toronto-St. Louis; or New York – London, not New York – Hicksville). You can listen to the full NPR broadcast below and find the transcript of the broadcast here.

Also for another take on this study, check out “How Twitter Proves That Place Matters” written by Richard Florida, in the Atlantic Cities.


[Update:  Since the NPR piece ran a few days ago, here are some interesting and unusual responses/interpretations of our study from around the web.]

§ Takhteyev, Y., Gruzd, A., & Wellman, B. (2012). Geography of Twitter networks Social Networks, 34 (1), 73-81 DOI: 10.1016/j.socnet.2011.05.006

The paper examines the influence of geographic distance, national boundaries, language and frequency of air travel on the formation of social ties on Twitter, a popular micro-blogging website. Based on a large sample of publicly available Twitter data, our study shows that a substantial share of ties lies within the same metropolitan region, and that for ties between regional clusters, distance, national borders and language differences all predict Twitter ties. We find that the frequency of airline flights between the two parties is the best predictor of Twitter ties. This highlights the importance of looking at pre-existing ties between places and people.