today: web – millions of users

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Today: Web – Millions of users. Web is like a “laboratory” for studying millions of people at once. Users leave detailed traces of their social activity. Large on-line applications with hundreds of millions of users. Connecting the dots…. - PowerPoint PPT Presentation

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Page 1: Today: Web – Millions of users
Page 2: Today: Web – Millions of users

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Today: Web – Millions of users

Large on-line applications

with hundreds of millions of

users

Users leave detailed traces

of their social activity.

Web is like a “laboratory” for

studying millions of people at once.

Page 3: Today: Web – Millions of users

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Connecting the dots…

As we connect the dots into a network patterns emerge...

Page 4: Today: Web – Millions of users

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Navigating the world’s social netowrk

The network: 180M people, 1.3B undirected edges

Page 5: Today: Web – Millions of users

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The 6 degrees of separation Small-world experiment [Milgram ‘67]

64 letters are sent-forward from Nebraska to Boston How many steps does it take?

Average path length is 6.26 degrees of separation

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Microsoft Instant Messenger(180M people, 1.3B undirected edges, )

Number of steps between 180

billion pairs of people

Avg. path length 6.690% of the people can be reached in

< 8 hops

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Use Machine Learning to find the target person

Green bar is prob. that node is good

Page 8: Today: Web – Millions of users

Information propagation on the web

Page 9: Today: Web – Millions of users

What does the web talk about? 1.6 million news media and blog sites 1. million articles a day What do they talk about? Who is imitating/copying whom?

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Info propagation on the web

News media writes articles and refer (link) to other articles and the information spreads

Can track the information as it spreads and mutates over millions

of websites

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Question…

= I have 10 minutes. Which news sites should I read to be most up to date?

= Who are the most influential bloggers?

?

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Problem: Covering blogs= Given a budget (e.g., of 3 blogs)= Select blogs to cover the most of

the blogosphere?= Bad news: Solving this

exactly is NP-hard= Good news: Theorem:

Can do it in linear time and within factor 3 of optimal

Blogosphere

“topics”

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So, who is influential?What should I read?

k Score Blog Posts InLinks OutLinks1 0.13 http://instapundit.com 4593 4636 52552 0.18 http://donsurber.blogspot.com 1534 1206 34953 0.22 http://sciencepolitics.blogspot.com 924 576 27014 0.26 http://www.watcherofweasels.com 261 941 36305 0.29 http://michellemalkin.com 1839 12642 63236 0.32 http://blogometer.nationaljournal.com 189 2313 92727 0.34 http://themodulator.org 475 717 49448 0.35 http://www.bloggersblog.com 895 247 102019 0.37 http://www.boingboing.net 5776 6337 618310 0.38 http://atrios.blogspot.com 4682 3205 310211 0.39 http://lawhawk.blogspot.com 1862 463 659712 0.40 http://www.gothamist.com 6223 3324 1717213 0.41 http://mparent7777.livejournal.com 25925 199 4793314 0.42 http://wheelgun.blogspot.com 1174 128 93915 0.43 http://gevkaffeegal.typepad.com/

the_alliance 302 428 2481

www.blogcascades.org