DM110 - Week 4 - Social Networks

DM110 Emerging Web Media Dr. John Breslin [email_address] http://sw.deri.org/~jbreslin/ Week 4: Social Networks

We all live in a social network…
… of friends, family, workmates, fellow students, acquaintances, etc.

Friend of a friend, or “dúirt bean liom go ndúirt bean leí”
Theory that anybody is connected to everybody else (on average) by no more than six degrees of separation
Everyone’s connected…

Milgram’s six degrees of separation theory
Sociologist Milgram conducted this experiment:
Random people from Nebraska were to send a letter (via intermediaries) to a stock broker in Boston
Could only send to someone with whom they were on a first-name basis
Among the letters that found the target, the average number of links was six
Stanley Milgram (1933-1984)

And now a major motion picture, kind of…
Six Degrees of Separation (1993)
“ I read somewhere that everybody on this planet is separated by only six other people. Six degrees of separation between us and everyone else on this planet. The President of the United States, a gondolier in Venice, just fill in the names... It’s not just big names — it’s anyone. A native in a rain forest, a Tiero del Fuegan, an Eskimo. I am bound — you are bound — to everyone on this planet by a trail of six people.”
Play from 1990 by John Guare

The Erdős number
Number of links required to connect scholars to Erdős via co-authorship of papers
Erdős wrote 1500+ papers with 507 co-authors
Jerry Grossman’s site allows mathematicians to compute their Erdős numbers:
http://www.oakland.edu/enp/
Connecting path lengths, among mathematicians only:
The average is 4.65
The maximum is 13
Paul Erdős (1913-1996)

Trying to make friends Valdis Marc Met Marc and I already had friends in common! I later found out my cousin Ailish also knows Andrew. The “small world” phenomenon… Latvia Uldis DERI John Dublin Clare Bros John C Andrew

“ It’s a small world after all!”, by Kentaro Toyama Kentaro Bash Karishma Sharad Maithreyi Anandan Venkie Soumya Prof. McDermott Ranjeet Prof. Sastry PM Manmohan Singh Prof. Balki Pres. Kalam Prof. Jhunjhunwala Dr. Montek Singh Ahluwalia Ravi Dr. Isher Judge Ahluwalia Pawan Aishwarya Ravi’s Father Amitabh Bachchan Prof. Kannan Prof. Prahalad Nandana Sen Prof. Amartya Sen Prof. Veni

The Kevin Bacon game (1)
Boxed version of the game
Invented by three Albright College students in 1994:
Craig Fass, Brian Turtle, Mike Ginelly
Goal is to connect any actor to Kevin Bacon, by linking actors who have acted in the same movie
The “Oracle of Bacon” website uses IMDB to find the shortest link between any two actors:
http://oracleofbacon.org/

Rod Stoneman (I) was in Falls, The (1980) with Patrick Whitney (I)
Patrick Whitney (I) was in Penn & Teller Get Killed (1989) with Nancy Giles
Nancy Giles was in Loverboy (2005) with Kevin Bacon

Total number of actors in database (as of yesterday):
832904
Average path length to Kevin:
2.97
Actor closest to “center”:
Rod Steiger (2.68)
Rank of Kevin, in terms of closeness to center:
1049th
Most actors are within three links of each other!

What are social network services?
Idea behind social networking services (SNS) is to make these real-world relationships explicitly defined online
Wikipedia:
“ A social network service is social software focused on the building and verifying of online social networks for whatever purpose.”
Surf from your list of friends to find friends-of-friends, or friends-of-friends-of-friends for various purposes
SNS are the new digital public places of Web 2.0
Most allow content generation and sharing
Gradual transformation of SNS to public e-markets

Features of social network services
Network of friends (inner circle)
Person surfing
Private messaging
Discussion forums
Events management
Blogging and commenting
Media uploading

Motivation for social network services
Allows a user to create and maintain an online network of close friends or business associates for social and professional reasons:
Friendships and relationships
Offline meetings
Curiosity about others
Business opportunities
Job hunting

Create new event
Search for NY people and invite guests
Choose all matches or friends only
Invitation and RSVP link sent automatically
Organise a regular networking event for members of a particular SNS living in New York:
Example: meet with local professionals

Create a network of parents to seek advice, offer help, and connect:
Filter your network of connections to see those with kids living in your area
Give this network a name, e.g. “Galway Parents’ Network”
Send your network of parents regular messages for support and advice
Example: creating a network for parents

Connected to any notable political figures?
Check the “shortest path”
If you know John then you are connected to Michael D. Higgins through John’s friend Iggy
Example: know any famous people?

Search for those who work in venture capital
Target those people working at firms of interest
View profiles to see common friends that can get you a meeting with the VC of choice
Try LinkedIn.com
You have a business idea and are looking for an “in” at a venture capital firm:
Example: finding venture capital

Find other NUI Galway singles with common interests and activities:
Search SNS for singles in your local area
Sort list to see pictures first
Find someone you like and send them a message from their profile
http://www.mulley.net/2006/07/23/how-to-use-google-to-get-a-girl-and-get-laid/
Example: networking for social purposes

History of online social networking
Up to 2003:
OneList, ICQ, Evite
2003 to 2005:
Friendster, orkut, LinkedIn
2005 to 2007:
Bebo, MySpace, YouTube
2007 to the future:
More later…

Big social network services
MySpace 130,000,000
Hi5 50,000,000
Xanga 40,000,000
Classmates.com 40,000,000
orkut 36,532,811
Windows Live Spaces 30,000,000
Friendster 29,100,000
Reunion.com 25,000,000
Bebo 22,000,000
BlackPlanet.com 18,000,000
Cyworld 15,000,000
Facebook 12,000,000
LiveJournal 10,921,263
http://en.wikipedia.org/wiki/List_of_social_networking_websites

orkut, Google’s SNS

Bebo, #200 in the world after just over a year

Klostu, a super social network of bulletin boards

Lots of venture capital for and sales of SNS sites
Friendster – $13M VC
Tribe – $6.3M VC
LinkedIn – $4.7M VC
Bebo – $15M VC (target audience is 10-20 years)
MySpace – Sold to News Corporation for $580M (target audience is 20-30 years)
Friends Reunited – Sold to ITV for £120M
Facebook – Purported $1B offer by Yahoo!, $1.6B actually available for deal, $2B wanted by founder

Can be many links even in a small-sized SNS
Meaningless when viewed as a whole, so need to apply some social network analysis (SNA) techniques:
“ Social Network Analysis: Methods and Applications”, Stanley Wasserman and Katherine Faust
http://www.socialnetworks.org/
http://lrs.ed.uiuc.edu/tse-portal/analysis/social-network-analysis/
http://vlado.fmf.uni-lj.si/pub/networks/pajek/
For example, can reduce the amount of relevant social network data by clustering
May choose to cluster people by common friends, by shared interests, by geography, by tags, etc.

What is social network analysis?
People are represented as nodes or “actors”
Relationships are represented as lines or edges:
Relationships may be acquaintanceship, friendship, co-authorship, etc.
Allows analysis using tools of mathematical graph theory, and mapping:
Movie actors
Scientists and mathematicians
Sexual interaction
Phone call patterns

Visualising your network of friends
You can graphically visualise your network of friends and friends-of-friends using various graphical tools
This is the friends network for “john b” (the ellipse in the center)
Surrounding him are his friends and friends-of-friends

Vizster, based on Prefuse

Social network analysis in use
Sociology theory applied to the 21st century, collecting data from social network websites:
http://www.zephoria.org/thoughts/archives/2006/08/19/research_on_soc.html
Combine with Semantic Web technologies to determine social behavioural patterns:
http://www.blogninja.com/galway-iswc2005.ppt
MIT Media Lab are conducting mobile SNA research via their “Reality Mining” project:
http://reality.media.mit.edu/

Knowing too much?
Individuals are revealing more and more information on SNS and other social software sites
Advertisers and marketers can gain better understanding from customer behavioural patterns
NSA using social network analysis technologies for homeland security
Personal privacy issues, where sensitive personal information is revealed on SNS
Analysing masses of social network information, “clouds” showing the overall picture
NSA also using “automated intelligence profiling” based on unreliable information

The future of social network services
Object-centered sociality:
http://www.zengestrom.com/blog/2005/04/why_some_social.html
Users connected via a common object, e.g. their job, university, hobby
SNS methods simulate real-life social interaction:
People meet others through something they have in common, not by randomly approaching each other
Better interaction methods with friends à la Second Life
Distributed social networks and reusable profiles:
Users may have many identities on different social networks, where each identity was created from scratch
Allow user to import existing identity, using a single global identity with different views (see FOAF and OpenID)

A distributed social network with FOAF
Can use FOAF to describe social networks across a number of services
Picture shows data from both boards.ie and my hand-coded FOAF file

Free social networking software
AroundMe
http://www.barnraiser.org/software_aroundme.php
Yogurt
http://sourceforge.net/projects/yogurt

References
“ Linked”, Albert-Laszlo Barabasi
“ Six Degrees”, Duncan J. Watts
Thanks:
http://www.csd.abdn.ac.uk/~fguerin/teaching/CS5038/assessment/essays_from_2006/groupC/GroupCsocial.ppt
http://research.microsoft.com/toyama/talks/2005%2009%2019%20Social%20Networks.ppt

DM110 - Week 4 - Social Networks

by John Breslin on Jan 31, 2007

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