Modeling the Spread of Influence on the Blogosphere

1
Modeling the Spread of Influence on the
Blogosphere

• Akshay Java, Pranam Kolari, Tim Finin, and Tim
  Oates
• UMBC Tech Report
• 04/12/06

2
Outline

• What is influence?
• Basic Influence Model
• Influence models for the blogosphere
• Results
• Conclusions

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What is Influence?

• Main Entry influence Pronunciation
  'in-"flü-n(t)s, esp Southern in-'Function
  nounEtymology Middle English, from Middle
  French, from Medieval Latin influentia, from
  Latin influent-, influens, present participle of
  influere to flow in, from in- fluere to flow --
  more at FLUID1 a an ethereal fluid held to
  flow from the stars and to affect the actions of
  humans b an emanation of occult power held to
  derive from stars2 an emanation of spiritual
  or moral force3 a the act or power of
  producing an effect without apparent exertion of
  force or direct exercise of command b corrupt
  interference with authority for personal gain4
  the power or capacity of causing an effect in
  indirect or intangible ways SWAY5 one that
  exerts influence- under the influence affected
  by alcohol DRUNK ltwas arrested for driving
  under the influencegt

NOT This Kind of Influence! -)
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Motivation

• Influence models studied for cocitation graphs
• David Kempe, Jon Kleinberg, Eva Tardos Maximizing
  the Spread of Influence through a Social Network,
  KDD 2003
• Applies to blogs also.
• Recent Examples Startups, Microsoft Origami,
  Walmart,DoD
• GOAL Predict influential blogs
• Target nodes to help achieve a Tipping Point

The Tipping Point Malcolm Gladwell
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Influence on the Blogosphere
Post was Influenced by NPR, eWeek
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Influence Models for the Blogosphere
Blog Graph
Influence Graph
1/3
U
2
2
1
3
3
2/5
1/3
V
1/3
1
1
1
1/5
5
5
2/5
4
4
1/2
1/2
Wu,v Cu,v / dv
U links to V gt U is Influenced by V
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Basic Influence Models
Influence Graph

• Linear Threshold Model
• S bvw ?v
• w is the active neighbor of v
• Cascade Model
• Pvw - probability with which a
• node can activate each of its
• neighbors, independent of
• history.

1/3
Active
2
1
3
2/5
1/3
?v
1/3
1
1
1/5
5
2/5
Active
4
Inactive
1/2
1/2
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Node Selection Heuristics

• Inlinks
• Easily spammed
• Centrality
• Expensive to compute for every large graphs
• PageRank
• Requires link information
• However, is easy to compute
• Greedy Heuristic
• Computationally expensive
• However performs better

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Effect of Splogs on Node Selection(indegree vs
pagerank)
Almost 54 of the links were from splogs/failed
to splogs/failed!
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Effect of Splogs on Inlinks
rank URL inlinks
1 http//www.livejournal.com/users/pics 3072
2 http//www.boingboing.net 2191
3 http//www.dailykos.com 2017
4 http//www.engadget.com 1942
5 http//profiles.blogdrive.com 1526
6 http//michellemalkin.com 1242
7 http//www.opinionjournal.com 1232
8 http//instapundit.com 1187
9 http//slashdot.org 1124
10 http//www.powerlineblog.com 909
11 http//www.huffingtonpost.com/theblog 905
12 http//corner.nationalreview.com 853
13 http//www.talkingpointsmemo.com 733
14 http//www.captainsquartersblog.com/mt 728
15 http//espn-presents2003-world-seriesofpoker.blogspot.com 711
16 http//3-world-series-of-poker-online-3.blogspot.com 711
17 http//worldseries-of-poker-network-tv-show.blogspot.com 711
18 http//wsop2003.blogspot.com 711
19 http//wsop-bracelet1.blogspot.com 711
20 http//worldseries-poker.blogspot.com 711
21 http//worldseries-of-poker-official.blogspot.com 711
22 http//worldseries-of-poker-wsop.blogspot.com 711
23 http//world-series-of-poker-nocd-patch66.blogspot.com 711
24 http//4-world-series-of-poker-past-winners.blogspot.com 711
25 http//7-wsop-games-7.blogspot.com 711
Tightly Knit Community of Splog
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Influence Models(without splog detection)
Number of nodes selected
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Influence Models (After splog removal)
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Influence Models(w.r.t. Technorati Ranks)
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Conlusions

• Influence models can be applied to blogs not just
  cocitation graphs
• Splogs are a problem
• Greedy heuristics work well, pagerank is an
  inexpensive approximation

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Ideas for CIKM 06

• Good or bad influence? Associating sentiment with
  links.
• Finding influential blogs for a topic. (SVM
  accuracy 75-85)
• Community structure of blogs.

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• Questions
• Comments/ Feedback?
• Thanks!
• Acknowledgement
• Buzzmetrics/Blogpulse for the dataset.