morning sessions at event today on social nets run by Assyst

This event: http://www.cnn.group.cam.ac.uk/news/scientific-meeting-on-social-networks-and-social-media-18th-january

Organised by: http://www.assystcomplexity.eu/
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Bernardo Huberman (HP)  - Getting Attention1. In last decade, web moved from download to 2-way2, Everyone has a megaphone (the interweb is one big ethernet?:-)3. attention is therefore the scarce resource attention is a coordination/rendezvous/synch mechanism anything except attention can be commodotized defn: attention in social terms (pagerank)4. Looking at this, we can build predictors and make money...5. Looked at Attention Seeking behaviours... doesn't matter if its your friends who applaud
Sanjeev Goyal - Contagion1. random v. smart attacks2. central v. distributed Net designer3. Design for resilience
Q (BH). can we filter spam on this basis/cost?(c.f. Ross work - can't afford email anymore) ------>
Maxi San Miguel  (IFISC) What can we learn from simple social behaviour models
isolate interaction mechanisms and find collective effectsfind causal relationsips...
one example: random imitation role of topology co-evolution heterogeneity in timing of interactionsExample: voters - imitation dynamics abosrbing states (all coloured red/green) when&how do we get (what about metastable case/oscillitory?) results anayltical for regular nets show ordering... in complex nets (small world or BA etc) , can get  non stable soln long range ties don't ctually help reachign agreement, counter-intuitive critical beaviour determined by mean node degree (c.f. haggle)dynamics of net (formation) & on the net (usage) but can we have co-evolution of agents and netrightwing view is net determis individual chocesleftwin view is individals constrined by social net :-) co-evol has model of agent/link changing/selected with distribution re-wiring rate v. use rate has critical phase changesheterogeneity in timing of individual activitie... empirically, we don't work at constant rate... so include a notion of node-specific internal  time..
Keys dimenaionality coevolution timingTakehomes strong messages dont homogenize, but polarize social interaction can lead to consenss different from external message
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Martin Everett - Manchester - dual project for 2 mode data
2 distinct groups - interaction netween group, not users in each group e.g. wikipedia & postersexample dataset women & southern events...problem - projection can lose data can we do directly? not necessarily...turns out (math says) there isn't much loss... can do SVD  makes it easy to find core/key eents,  and key people in women/southern fried chicken e.g. and various other clustering things...can use this to find centrality- discover key agents in women getting other women to events
takehome -  ignore incorrect folkore about losing info in this approach...

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Ross Anderson (CL) Temporal Node Centrality - work with hyoungschick kim

 

starting with attacks/defense on scale free net hubs etc....

 

results in papers by Hyoungschick et a...

 

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Cecilia Mascolo (CL) Geo-spatial

Case study - add in geo-info (like foursquare) - with geo-tagging of postsm can see where messages/interactions occur.

 

questions of interest -

1. relation twixt geo-distance and social distance - for example

2. distance and degree

Applications - can we exploit geo-spatial info to build better social apps and systems?

1. link prediction....

2. movement model/prediction

Q&A for morning session chaired by Y.T. (for readers of snow crash:)

 

Someone more sociable than I can blog the pm:)