1. The Convergence of Social and Technological Networks By Jon Kleinberg Presented by Jonathan Willitts

2. 2 Contents  Overview  Why look into convergence of networks  How it is possible  The small world phenomenon  Social contagion and the spread of ideas  Further directions

3. 3 Overview  Past decade has witnessed a coming together of the technological networks that connect computers on the Internet, and the social networks that have linked humans for millennia  Sites such as Facebook, MySpace, Wikipedia, digg, del.icio.us, YouTube and flickr have all developed from this  Growing Pattern of movements to: Form connections with others,Form connections with others, Build virtual communitiesBuild virtual communities Engage in self expressionEngage in self expression  Data being generated by these online worlds allows us to observe human social interaction in a way never previously possible

4. 4 Why look into convergence of networks?  Images of social networks offer glimpses of everyday life from an unconventional vantage point, such as: Flow of information through an organisationFlow of information through an organisation Disintegration of social groups into rival factionsDisintegration of social groups into rival factions  Science advances when we can take something that was once invisible, and make it visible  This is now happening with social networks, and social processes

5. 5 How it is possible?  Collecting data on social networks has previously been hard work, requiring: Extensive contact with group being studiedExtensive contact with group being studied Limited to much smaller groups (tens or hundreds of individuals)Limited to much smaller groups (tens or hundreds of individuals)  Online social interactions however leave digital traces  This allows us to collect and use minute by minute data on tens of millions of people to: Monitor the way people seek connections and form friendships (Facebook)Monitor the way people seek connections and form friendships (Facebook) Coordinate with and engage in creative expressions (Wikipedia or flickr)Coordinate with and engage in creative expressions (Wikipedia or flickr) Observe news stories / witness controversy gathering around communities (bloggers)Observe news stories / witness controversy gathering around communities (bloggers)

6. 6 The Small-World Phenomenon / Decentralised Search  Stanley Milgram experiments in the 1960s  Milgram asked a few hundred people in Boston and the Midwest to direct a letter towards a stockbroker in Massachusetts Gave each the targets name, address and occupationGave each the targets name, address and occupation Only mail letter to someone they knew on first name basisOnly mail letter to someone they knew on first name basis Mail with instructions to pass the letter onMail with instructions to pass the letter on  Successful letters reached the target in a median of 6 steps  Play and then film: Six Degrees of Separation  Game: Six Degrees of Kevin Bacon

7. 7 Six Degrees of Separation

8. 8 Other work (MSN Messenger)  Social network built from quarter-billion instant messaging accounts  Connected individuals who engaged in a conversation over a 1 month period  Average length of the shortest path between any two people was 6.6  Very close to Milgram’s figure, obtained completely differently Milgram asked targets to forward letter to people they think might know the targetMilgram asked targets to forward letter to people they think might know the target Studying “random” links made by conversations, participant unaware.Studying “random” links made by conversations, participant unaware.

9. 9 Milgram Findings  Milgram experiment not only showed that paths existed, but also that people knew how to find them  People asked to find the target couldn’t know the course the letter would take, or whether it would get there  The fact that so many did shows social networking ability to funnel information towards far away targets  Caveat: the experiments were more successful the more affluent and socially accessible the target  Many chains failed to complete

10. 10 Nexus graph http://nexus.ludios.net

11. 11 Social contagion and the spread of ideas  Milgram’s experiments aimed to focus messages on particular targets  Information on social networks tends to radiate out in many directions at once  Rumours, political messages and online videos can spread contagiously from person to person similar to an epidemic

12. 12 Diffusion of innovations  There is a pattern by which people influence each other over periods of time (both online / offline) to form new political and social beliefs,form new political and social beliefs, adopt technologies andadopt technologies and change personal behaviourchange personal behaviour  Process known as “Diffusion of Innovations”  Whilst outcomes may be clearly visible, the inner workings have remained unknown

13. 13 Recent studies of contagion  The probability of purchasing of books, DVDs and music from a large online retailer increased with the number of email recommendations a potential customer received  Probability of joining a group in an online community increases the more friends are already a member of the group  There is however a “diminishing returns” pattern in which the marginal effect of each successive friend decreases.

14. 14 Contagion as a design principle  Decentralised search problem at the heart of the small world phenomenon  Contagion in networks serves as a design principle for spread of information  Early distributed computing work proposed notion of “epidemic algorithms” where information updates would be spread between hosts using a probabilistic contagion rule  Lead to further research based on the fact that these algorithms can be highly robust and simple to configure at each node

15. 15 Further directions  Whilst most of this presentation has been focussed on dynamic behaviour of individuals in social networks, an important complimentary areas is how the structure of the network itself evolves over time  Recent studies of large datasets have shed light on important principles of network evolution such as: Preferential attachment: in which nodes that already have many links will tend to acquire further ones at a greater ratePreferential attachment: in which nodes that already have many links will tend to acquire further ones at a greater rate Triadic closure: links are more likely to form between two people when they have a friend in commonTriadic closure: links are more likely to form between two people when they have a friend in common Densification effects: in which the number of links per node increases as the network growsDensification effects: in which the number of links per node increases as the network grows Shrinking diameters: in which the number of steps in the shortest path between nodes can actually decrease as the total number of nodes increasesShrinking diameters: in which the number of steps in the shortest path between nodes can actually decrease as the total number of nodes increases