Exploring Virtual Social Interactions and Human Connections

1. Are You moved by Your Social Network Application? AbderrahmenMtibaa, AugustinChaintreau, Jason LeBrun, Earl Oliver, Anna-KaisaPietilainen, Christophe Diot Thomson Paris Research Lab Avinash Patlolla

2. Outline • Introduction • Motivation • Experimental setup • Terminology and Definitions • Topological comparisons • Node properties • Contact properties • Path properties • Social forwarding paths • Summary and critiques

3. Outline • Introduction • Motivation • Experimental setup • Terminology and Definitions • Topological comparisons • Node properties • Contact properties • Path properties • Social forwarding paths • Summary and critiques

4. Introduction • Before the Internet: socialize by physical meeting • Today: Internet allows “virtual” socializing • Tomorrow: Meet the virtual community using opportunistic contacts and locality

5. Motivation • Explore the relation between virtual social interactions and human physical meetings • Understand complex temporal properties based on simple social properties • Forwarding based on social network properties

6. Outline • Introduction • Motivation • Experimentalsetup • Terminology and Definitions • Topological comparisons • Node properties • Contact properties • Path properties • Social forwarding paths • Summary and critiques

7. Experimental Setup • Distributed smartphones with mobile opportunistic social networking application to 28 participants (but later reduced to 27) • 3 days experiment at CoNextDecember ‘07 • Initially, each participant was asked to identify friends among the 150 CoNext participants. • Applications: • Opportunistic socializing: make new friends based on friends • Asynchronous messaging

8. Outline • Introduction • Motivation • Experimental setup • Terminology and Definitions • Topological comparisons • Node properties • Contact properties • Path properties • Social forwarding paths • Summary and critiques

9. Terminology and Definitions • Social graph: Graph of friendship between participants. Denoted as G = (V, E) • Contact graph: Collection of opportunistic Bluetooth contacts between the participants form the temporal network , which is called contact graph. Denoted as Gt = (V, Et) • Delay- optimal path: A path, in contact graph, from sto dstarting at time t0 is delay-optimal if it reaches the destination din the earliest possible time. The delay optimal path can be computed via dynamic programming

10. Outline • Introduction • Motivation • Experimental setup • Terminology and Definitions • Topologicalcomparisons • Node properties • Contact properties • Path properties • Social forwarding paths • Summary and critiques

11. Topological comparison

12. Node properties • Characterize Node heterogeneity • High/low activity • Popularity • Contact rate • Two metrics are measured • Node degree • Social graph: number of friends • Contact graph: average number of devices seen per scan (every 2 min.) • Centrality of nodes: • Social graph: measure the occurrence of the node inside all shortest paths • Contact graph: measure the occurrence of the node at each time t inside all shortest paths

13. Node degree Ordering error =

14. Centrality of nodes

15. Contact properties • Compare contact according to: • Social distance (friends have distance 1, friends of friends of friends have distance 2 and so on) • time between two successive contacts

16. Path properties • Delay-optimal paths as a function of the social distance between the source and the destination

17. Outline • Introduction • Motivation • Experimental setup • Terminology and Definitions • Topological comparisons • Node properties • Contact properties • Path properties • Social forwarding paths • Summary and critiques

18. Social forwarding paths • General model: depending on the source sand the destination d, a rule defines a subset of directed pairs of nodes (uv) so that only the contacts occurring for pairs in the subset are allowed in forwarding path. • Path construction rules: • neighbor(k): (uv)is allowed if and only if uand vare within distance kin the social graph • destination-neighbor(k): (uv) is allowed if and only if vis within distance kof d • non-decreasing-centrality: (uv) is allowed if and only if C(u) <= C(v) • non-increasing-distance: (uv) is allowed if and only if the social distance from vto dis no more than the one from uto d

19. Performance of different path construction rule

20. Comparison of rules • The neighbor rule performs reasonably well • The rule based on centrality outperforms all the other rules considered • The combination of neighbor and centrality rules reduce the cost (offers best trade-off)

21. Outline • Introduction • Motivation • Experimental setup • Terminology and Definitions • Topological comparisons • Node properties • Contact properties • Path properties • Social forwarding paths • Summary and critiques

22. Summary and Critiques • Similarity in the properties of nodes, contacts and paths in the two graphs • Highlighted the importance of centrality of nodes • Using social neighbors to communicate can be effective to exchange messages with opportunistic bandwidth • Critiques: • Important issues not yet studied, like computing centrality of nodes in a distributed manner. • Scalability and usability • Not many technical details

23. References • http://www.docstoc.com/docs/5083899/Are-You-moved-by-Your-Social-Network-Application Questions???