I256:%20Applied%20Natural%20Language%20Processing

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I256 Applied Natural Language Processing
Marti Hearst Nov 8, 2006    
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Today

• Comparing term clustering and category output
• Clustering in Weka
• Data mining from blogs

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LDA

• Latent Dirchelet Allocation
• Blei, Ng, Jordan, JLMR 03.
• LDA is a hierarchical probabilistic model of
  documents.
• LDA allows you to analyze of corpus, and extract
  the topics that combined to form its documents.
• http//www.cs.princeton.edu/blei/lda-c/
• Not really clustering, but in the soft
  clustering ballpark.

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LDA on Recipes

• http//orange.sims.berkeley.edu/cgi-bin/flamenco.c
  gi/recipes-newblei/Flamenco

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LDA on Recipes

• http//orange.sims.berkeley.edu/cgi-bin/flamenco.c
  gi/recipes-newblei/Flamenco

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CastaNet

• (Semi)automated facet creation
• Stoica Hearst
• Build up from WordNet
• Algorithm is fully automatic but we think you can
  improve results manually afterwards.

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CastaNet on Recipes

• http//orange.sims.berkeley.edu/cgi-bin/flamenco.c
  gi/recipes-automated/Flamenco

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CastaNet on Recipes

• http//orange.sims.berkeley.edu/cgi-bin/flamenco.c
  gi/recipes-automated/Flamenco

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TopicSeek on Enron Email

• Technique pLSI (probabilistic LSI, Hofmann 99)
• Hand-picked example for website
• http//topicseek.com/enron.html

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TopicSeek on Medline

• Technique pLSI (probabilistic LSI, Hofmann 99)
• Hand-picked example for website
• http//topicseek.com/pubmed.html

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CastaNet on Medline Journal Titles

• http//orange.sims.berkeley.edu/cgi-bin/flamenco.c
  gi/medicine-automated/Flamenco

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Clustering in Weka
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Looking at Clustering Results

• Weka lets you save cluster results to an ARFF
  file
• I wrote some python code to process this file and
  pull out the Subject headings for each newsgroup
  posting in each cluster.

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15-way clustering
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Cobweb clustering
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Blog Analysis

• Whats special about blogs?

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Blog analysis sites

• http//dijest.com/bc/
• Called blogcount lots of stats and news about
  blogs
• http//blogcensus.net/?pagetools
• Language, location, marketshare
• http//www.perseus.com/blogsurvey/
• Stats about biggest blogs, demographics
• http//www.weblogs.com/
• Notify when new content posted
• http//blogpulse.com/
• Trends and recent popular topics

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Blogs vs. Newsgroups

• Posting about products what can we tell?
• Blog
• Newsgroup

Example from Glance, Hurst, and Tomokiyo 04
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Analyzing Blogs for Market Data

• Idea examine comments about a product (or a
  products competition or market) in an automated
  fashion.
• Application area handheld electronic devices.

Figure from Glance, Hurst, Nigam, Siegler,
Stockton, Tomokiyo, KDD05
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Analyzing Blogs for Market Data
Figure from Glance, Hurst, Nigam, Siegler,
Stockton, Tomokiyo, KDD05
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Technology used

• Post segmentation
• Important phrases
• Foreground vs. background corpus
• Background text about product
• Foreground certain negative paragraphs about
  product
• Sentiment classification
• What do people talk about when saying negative
  things about product X?
• Social network analysis (on discussion boards)
• What does this group of people talk about when
  saying negative things about product X?
• Author dispersion
• Many people talking about it, or just a few?

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Example

• What common phrases to people use when saying
  negative things about product X?

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Example

• What do people in this group say when saying
  negative things about product X?

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Example

• What do people in this group say when saying
  negative things about product X?

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Predicting Film Sales

• Idea
• Use discussion before a film to predict its
  opening weekend box office scores
• Use discussion afterwards to predict longer-term
  sales
• Separate out topic labels from sentiment labels
• Outcome
• Good predictor for opening weekend, but not for
  longer term
• Observation the nature of discussion gets (and
  thus harder to analyze) after the film has been
  out a while.

Example from Mishne Glance, 2006
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Predicting Film Sales
Example from Mishne Glance, 2006
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Prediction Film Sales
Example from Mishne Glance, 2006
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Predicting Film Sales
Example from Mishne Glance, 2006
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Analyzing Political Blogs

• Analyze
• Who links to whom
• What the popularity profile looks like
• A powerlaw/Zipf/Pareto, of course
• Look at structure of topic-specific blogs
• By inbound links

Image from blogsphere ecosystem via Shirky
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Analyzing Political Blogs

• Earlier work examined books bought together in
  pairs at major retailers
• Krebs, Divided we Stand??? http//www.orgnet.com/l
  eftright.html
• In other domains the groupings are more
  distributed.

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http//www.orgnet.com/booknet.html
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http//www.orgnet.com/leftright.html from Jan 2003
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http//www.orgnet.com/divided.html from 2004
election
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Analyzing Political Blogs

• Study by Adamic and Glance, 2005
• Analyzed 40 most popular political blogs
• 2 months preceding 2004 US presidential election
• Also study 1000 political blogs on a one day
  snapshot
• Findings for the latter
• Liberal and conservative blogs had distinct lists
  of favorate news sources, people, and topics,
  with some overlap on current news
• Use labels from aggregator sources
• Linking patterns were indeed pretty internal (91
  stayed within political leaning)
• More and more frequent linking among
  conservatives
• 82 conservative linked out vs. 74 of liberal

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Analyzing Political Blogs

• For the 40 most popular blogs
• Looked for echo chamber effect
• The conservative blogs are more tightly
  interlinked.
• Question do they repeat the same concepts more?
• Measured textual similarity among blog posts
• Slightly stronger within a political leaning than
  between, but not one orientation more than the
  other.
• Looked for interaction with mainstream media
• Found strong distinctions between which sources
  cited

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Image from Adamic Glance 200
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Image from Adamic Glance 200
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Image from Adamic Glance 200
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Image from Adamic Glance 200
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Image from Adamic Glance 200
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Image from Adamic Glance 200
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Next Time

• Sentiment and Opinion Analysis