Quantifying locality in complex social networks

Quantifying locality in complex social networks

Gábor Vattay

Departmant of Physics of Complex Systems

Eötvös University Budapest

My coworkers

• István Csabai István professzor

• Dániel Kondor Ph.D., MIT

• Eszter Bokányi graduate student

• László Dobos assistant professor

• Szüle János graduate student

• Kallus Zsófia graduate student

• Sebők Tamás graduate student

• Barankai Norbert graduate student

a SZOCIOLÓGIA mint

TERMÉSZETTUDOMÁNY

Twitter API

DB

PlanetLab nodes

User status updates

Indexed geo data

User connections graph

User Graph Discovery

Tool

Data Processing Framework

Our database2012-2014

4.0 Billion tweets

1.6 Billion GPS

130 Million users

Twitter friendship

Top 6 Million GPS

122 Million Friendships

Twitter friendship map @elte

Milgram’s small world experiment

Figure 4. Number of steps needed to reach the proximity of target users.

Szüle J, Kondor D, Dobos L, Csabai I, et al. (2014) Lost in the City: Revisiting Milgram's Experiment in the Age of Social Networks. PLoS ONE 9(11): e111973. doi:10.1371/journal.pone.0111973http://www.plosone.org/article/info:doi/10.1371/journal.pone.0111973

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0111973

Clustering algorithms

Table 1. Regional graphs.

Kallus Z, Barankai N, Szüle J, Vattay G (2015) Spatial Fingerprints of Community Structure in Human Interaction Network for an Extensive Set of Large-Scale Regions. PLoS ONE 10(5): e0126713. doi:10.1371/journal.pone.0126713http://journals.plos.org/plosone/article?id=info:doi/10.1371/journal.pone.0126713

http://journals.plos.org/plosone/article?id=info:doi/10.1371/journal.pone.0126713

Fig 2. Clustering of the United Kingdom.



Fig 3. Clustering of the subgraph of Canada.



Fig 4. Clustering of the subgraph of the Continental US.



Fig 5. Second level partitioning of the Western US cluster.



Fig 6. Clustering of the countries of South America.



Fig 7. Clustering of the 28 member countries of the European Union combined with second-level results.



Fig 8. Clustering of the countries of the European continent combined with second-level results.



Fig 9. Communities formed in Switzerland.



Fig 10. Communities formed in Cyprus and Greece.



Fig 11. Communities formed in Germany and Turkey.



Fig 12. Clustering of the Former Yugoslavia.



Fig 13. Clustering of Spain.



Fig 14. Clustering of France.



Fig 15. Clustering of Germany.



Fig 16. Clustering of the region of Southeast Asia with inclusion of China and Japan.



Fig 17. Clustering of Japan.



Fig 18. Clustering of India.



THANK YOU!

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Science

Quantifying locality in complex social networks