Analyzing the Political Blogosphere

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Analyzing the Political Blogosphere

• .

19 March 2007
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Social Media

• Social media describes the online tools and
  platforms that people use to share opinions,
  insights, experiences, and perspectives -
  wikipedia
• Level of user participation and thought sharing
  across varied topics

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Blogs Essence of Social Media
Blogs spread new ideas and information rapidly
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Knowing Influencing your Audience

• Your goal is to campaign for a presidentialcandid
  ate
• How can you track the buzz about him/her?
• What are the relevant communities andbogs?
• Which communities are supporters, which are
  skeptical, which are put off by the hype?
• Is your campaign having an effect? The desired
  effect?
• Which bloggers are influential with political
  audience? Of these, which are already onboard and
  which are lost causes?
• To whom should you send details or talk to?

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Influence Detection

• Often voters are influenced by opinions and
  reviews on blogs
• Detecting influential nodes and their role in how
  people perceive a political party could be an
  important tool during campaigning
• Using topic, social structure, opinions, biases
  and temporal information we can develop an
  accurate model for influence

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Influence in Communities
http//michellemalkin.com/
http//instapundit.com
http//dailykos.com
http//volokh.com
http//crooksandliars.com
http//rightwingnews.com
Communities detected using Fast algorithm for
detecting community structure in networks, M.E.
J. Newman
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Influence of MSM

• Citation count alone is not an indicator of
  influence who cites is a factor.

Using a list of 130 dem and 140 rep blogs
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Computing Influence of MSM

• For Democratic Citations
• Score(i) Pd(i)log(Pd(i)/Pr(i))Nd(i)
• where
• i is the MSM source
• Pd(i) probability that a democratic blog links
  to MSM i
• Pr(i) probability that a republican blog links
  to MSM i
• Nd(i) number of distinct democratic blogs
  linking to i
• Similar ranking for republican blogs

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Opinions in Social Media
Readers Perspective Starbucks Sandwiches are
bad!

• TREC 06 Finding opinionated posts, either
  positive or negative, about a query
• 2006 TREC Blog corpus
• 80K blogs
• 300K posts
• 50 test queries
• Challenges open domain sentiment words, slangs,
  subject

• I went to school early so I would have time to
  grab some lunch. Which ended up consisting of a
  crappy sandwich from starbucks and a chai latte.
  Lacey came into Starbucks while I was there so we
  chatted for a little bit and she thought that I
  might be in her class. After I finished eating I
  headed to school and checked the board..1

Narrative
Expressed Opinions
Opinions can effect buying decisions of customers
1 http//annamay13x.livejournal.com/7061.html
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Finding Feeds That Matter
Analysis of Bloglines Feeds 83K publicly
listed subscribers 2.8M feeds, 500K are unique
26K users (35) use folders to organize
subscriptions Data collected in May 2006
Before Merge
After Merge
http//ftm.umbc.edu
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Finding Feeds That Matter

• Top Feeds for Politics (Merging political,
  political blogs)
• Talking Points Memo by Joshua Micah Marshall
• Daily Kos State of the Nation
• Eschaton
• The Washington Monthly
• Wonkette, Politics for People with Dirty Minds
• http//instapundit.com/
• Informed Comment
• Power Line
• AMERICAblog Because a great nation deserves the
  truth
• Crooks and Liars

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Finding Feeds That Matter

• Tag Based Feed Recommender Feeds under similar
  folder names
• http//www.dailykos.com
• Recommended Feeds
• http//www.andrewsullivan.com/index.php
  http//www.talkingpointsmemo.com/
  http//atrios.blogspot.com
• http//jameswolcott.com/
• http//mediamatters.org/ http//yglesias.type
  pad.com/matthew/
• http//billmon.org/
• http//digbysblog.blogspot.com
• http//instapundit.com/
• http//www.washingtonmonthly.com/

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Finding Influential Feeds using Co-Citations
www.dailykos.com
Feed recommendations
Blogs influenced by seed set
Leading blogs about Politics. Seed set is top
blogs in politics from bloglines and blog graph
used is from Blogpulse dataset..
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Link Polarity / Bias

• Linking alone is not indicator of influence
• Polarity can indicate the type of influence
• Consistent negative / positive opinion over a
  period of time can indicate bias
• Link polarity/citation signal can also be helpful
  in determining trust

Strong Negative Opinion
Mildly Negative opinion
Republican Blog
Democrat Blog
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Modeling Influence Using Link Polarity

• Motivation
• Growing interest in exploring role of communities
  in social media
• Better community detection algorithms using
  sentiment associated with links
• Convert sparsely connected blog graph into a
  densely connected one with sentiment weight
  attached to every link
• Approach
• Link Polarity Analyze post text surrounding
  links to determine bias of bloggers about each
  other
• Trust Propagation Use trust propagation models
  to spread the polarity from a small subset of
  connected bloggers to all bloggers.
• Experiments
• Study political blogosphere with goal to classify
  blogs as left/right leaning
• Bias detection using positive/neural/negative
  score from influential bloggers (high in-link
  blogs) in both communities
• Validation with a hand-labeled dataset indicates
  60 correct classification

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Birds Eye View Step 1
E
C
B
D
foo
F
A

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Birds Eye View Step 2
E
C
B
He is great
D
What crap!
foo
I like him
ridiculous
F
A
-ve bias
ve bias

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Birds Eye View Step 3
E
C
B
D
foo
F
A
-ve bias
ve bias

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Birds Eye View Step 4
E
C
B
D
foo
F
A
-ve bias
ve bias

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Birds Eye View Step 4
E
C
B
D
foo
F
A
-ve bias
ve bias

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Link Polarity Example

• Stephen Colbert's performance at the White House
  Correspondents' Association dinner has garnered
  him huge applause in the blogosphere and also on
  C-Span where it was shown more than once. Those
  of us who have been angry with Bush for quite
  some time because of his arrogant and feckless
  corruption of our country were even more thrilled
  to see and know that he had no recourse but to
  sit there and watch his aspirations for greatness
  be destroyed by a master of irony.
• This will be his legacy I stand by this
  man. I stand by this man because he stands for
  things. Not only for things, he stands on things.
  Things like aircraft carriers and rubble and
  recently flooded city squares. And that sends a
  strong message, that no matter what happens to
  America, she will always rebound -- with the most
  powerfully staged photo ops in the world. We who
  have been watching Stephen Colbert eviscerate
  politicians that have come on his show knew he
  was a gifted comedian. But it took Saturday's
  dinner to demonstrate how incredibly effective
  the art form Colbert has chosen is for exposing
  the Potemkin Regime Bush and his henchmen have
  created. Rove and the right wing machine have no
  answer to the performance but to say "it bombed",
  "it wasn't funny", and to hope that by ignoring
  it, the caustic cleansing agent it has lobbed
  into their camp can be contained. Yet, the
  Republican spinmeisters are the masters of
  spin.2
• This - http//dailykos.com/storyonly/2006/4/30/1
  441/59811
• Np 8, Nn 4 Polarity 0.33
• 2http//www.pacificviews.org/weblog/archives/00
  1989.html

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Trust Propagation

• Based on Guhas work on propagating trust and
  distrust
• Mij represents bias from user i to j (0 lt Mij lt
  1)
• Belief matrix M represents the initial set of
  known beliefs
• Mij can be based on trust matrix (T), distrust
  matrix (D) or a combination of trust and distrust
  (T-D) from i to j.
• T Positive Polarities and D Negative
  Polarities
• Goal is to compute all unknown values in M
• Results from validations on dataset from
  epinions are impressive
• 1 Guha R, Kumar R, Raghavan P, Tomkins A.
  Propagation of trust and distrust. In Proc. 13th
  Int. World Wide Web Conf., New York, NY, USA, May
  2004. ACM Press, 2004.

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Experiments

• Domain
• Political Blogosphere
• Dataset from Buzzmetrics2 provides post-post
  links over 1.5M posts
• Few off-the-topic posts help aggregation
• Potential business value
• Reference Dataset
• Adamics 3 Hand-labeled dataset classifies
  blogs as right or left leaning
• Timeframe 2004 presidential elections, over 1500
  blogs analyzed
• Overlap of 300 blogs between Buzzmetrics and
  reference dataset
• Goal
• Classify the blogs in Buzzmetrics dataset as
  democrat and republic and compare with reference
  dataset

• 2 Lada A. Adamic and Natalie Glance, "The
  political blogosphere and the 2004 US Election",
  in Proceedings of the WWW-2005 Workshop, MAY
  2005. Buzzmetrics www.buzzmetrics.com

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Effect of Link Polarity
Trust propagation on polar links more effective
than on non-polar.
Republican blogs classified more correctly
Link Polarity yields 30 classification
improvement
Convergence after 20 propagations
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Effect of text window size

• Optimal window size is 750 characters for our
  experiments
• Small window size Non-opinionated phrases
• Large Window size Analysis of non-related text
• Specific to our experiments, numbers may not be
  generalized

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Sample Data

• Trust propagation compensates for initial
  incorrect polarity (DKAT)
• Trust propagation doesnt change correct polarity
  (AT-DK)
• Trust propagation assigns correct polarity for
  non-existent links (AT-IP)
• Numbers in italics problematic (AT-MM)
• Make polarities below threshold zero?
• Improve sentiment detection?

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Future Work

• Bias and trustworthiness of MSM sources
• Trend extraction and meme tracking for political
  blogs
• Real time classification positive and negative
  opinions for presidential candidates
• Determining genres in political opinions using
  content analysis.