Blog, Forum or Newspaper? Web Genre Detection using SVMs Philipp Berger, Patrick Hennig, Martin Schönberg, and Christoph Meinel Hasso Plattner Institute 06.12.2015
Project Scope
■ Prototype called Blog Intelligence ■ Several million blog posts ■ Personalized Analysis of the whole corpus ■ Meaningful Visualizations ■ Smart Search Engine ■ blog-intelligence.com
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Blog, Forum or Newspaper?
■ Web genre detection task ■ Blogs become a versatile publishing platform □ Personal blogs □ Community blogs □ Forums □ News portals □ Homepages □ Shopping Portals □…
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Amazing Variety Corporate Blogs vs. Blog Communities
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Amazing Variety Fashion Blog vs News Portal
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Amazing Variety News Communities vs. Travel Blogs vs. Cooking Blogs
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Definition is Key - Our Perspective ■ What is … □ … a blog? – Diary-like website from one or more authors – Creates a social graph by linking called blogosphere
□ … a forum? – Multiple users discuss on various threads – High diversity of authors
□ … a news portal? – High number of authors / one pseudonym – High number of articles – More objective
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Related Work Automatic Website Categorization ■ SVMs for the Blogosphere Blog Identification and Splog Detection ■ Pranam Kolari, Akshay Java, Tim Finin, Tim Oates, Anupam Joshi University of Maryland Baltimore County, 2006 ■ “Is this a blog or not?” ■ ~97% F-Measure ■ ● 2600 manually annotated blogs ● Support Vector Machines ● Cross Validation ● 9 years ago
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General Approach ML-supported Classification (SVM)
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Feature Pool Ngrams
■ Extract the most significant ngrams (size 4-6) ■ Restrict to text areas □ content □ links □ page url □ title □ anchor tags
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Feature Pool Human curated keywords □ Title and URL
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Feature Pool
Website clues and ratios ■ Social links to □ Facebook, GooglePlus, Twitter, Youtube ■ Search boxes ■ Text areas and submit buttons (comment section) ■ #Links to length of text ■ #Images to length of text ■ #Videos to length ftext
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Problem of SVM Evaluation Many Parameters and Folds… ■ 22040 parameter combination
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Evaluation
Spinn3r Dataset
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Evaluation Single Features
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Evaluation Single Features
■ Best Single Features □ ngram of content only has already accuracy of 78% □ Manual keywords only 50% accuracy
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Evaluation
Combinations
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Evaluation
Combinations
■ Ngram-based classification already has overall accuracy of 78% ■ Highest accuracy 83.5% overall categories □ Best features – Ngrams of content – Ngrams of URLs – Quanitities (number of links, images, …)
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□ No manual keywords and ratios
Conclusion
■ Definition of categories for blog-like websites ■ Implemented various features ■ Extensive evaluation ■ 83.5% overall accuracy
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