DM110 - Week 4 - Social Networks
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DM110 Emerging Web Media / Huston Film School, National University of Ireland, Galway / 30th January 2007

DM110 Emerging Web Media / Huston Film School, National University of Ireland, Galway / 30th January 2007

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  • 1. DM110 Emerging Web Media Dr. John Breslin [email_address] http://sw.deri.org/~jbreslin/ Week 4: Social Networks
  • 2. We all live in a social network…
    • … of friends, family, workmates, fellow students, acquaintances, etc.
  • 3.
    • 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…
  • 4. 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)
  • 5. 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
  • 6. 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)
  • 7. 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
  • 8. “ 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
  • 9. 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/
  • 10. The Kevin Bacon game (2)
    • 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
  • 11. The Kevin Bacon game (3)
    • 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!
  • 12. 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
  • 13. Features of social network services
    • Network of friends (inner circle)
    • Person surfing
    • Private messaging
    • Discussion forums
    • Events management
    • Blogging and commenting
    • Media uploading
  • 14. 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
  • 15.
    • 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
  • 16.
    • 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
  • 17.
    • 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?
  • 18.
    • 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
  • 19.
    • 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
  • 20. 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…
  • 21. 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
  • 22. orkut, Google’s SNS
  • 23. Bebo, #200 in the world after just over a year
  • 24. Klostu, a super social network of bulletin boards
  • 25. 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
  • 26. 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.
  • 27. 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
  • 28. 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
  • 29. Vizster, based on Prefuse
  • 30. 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/
  • 31. 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
  • 32. 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)
  • 33. 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
  • 34. Free social networking software
    • AroundMe
      • http://www.barnraiser.org/software_aroundme.php
    • Yogurt
      • http://sourceforge.net/projects/yogurt
  • 35. 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