#SDoW2011 Keynote: User Modeling and Personalization on Twitter

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Keynote at http://sdow.semanticweb.org/2011/

Transcript of #SDoW2011 Keynote: User Modeling and Personalization on Twitter

  • User Modeling and Personalizationon TwitterSDoW, ISWC, Bonn, Oct 23, 2011 Fabian Abel Web Information Systems, TU Delft Delft University of Technology
  • #papers that use Twitter datasets 2006 2007 2008 2009 2010 2011 2012 time User Modeling and Personalization on Twitter 2
  • Perspectives on Twitter data Grrrrthat is gr8 http://bit.ly/47gt3 @bob What are Bobs personal interests? What are his current demands?... User Modeling and Personalization on Twitter 3
  • What we do: Science and Engineering for the Personal Webdomains: news social mediacultural heritage public datae-learning Personalized Personalized Adaptive Systems Recommendations Search Analysis and User Modeling Semantic Enrichment, Linkage and Alignment user/usage data Social Web User Modeling and Personalization on Twitter 4
  • User Modeling Challenge Personalized News Recommender Profile I want my ? personalized news recommendations! Analysis and User Modeling Semantic Enrichment, (How) Linkage and Alignment can we infer a Twitter- based user profile that supports a news recommender? User Modeling and Personalization on Twitter 5
  • QiGao Geert-Jan Houben Ke TaoFabian, Qi, Geert-Jan, Ke: Analyzing User Modeling on Twitterfor Personalized News Recommendations. UMAP 2011User Modeling FrameworkBuilding Blocks for generating valuable user profiles User Modeling and Personalization on Twitter 6
  • User Modeling Building Blocks 1. Temporal Constraints Profile? (a) time period1. Which tweets of concept weightthe user should be analyzed? ? (b) temporal patterns start weekends end Morning: Afternoon: time Night: June 27 July 4 July 11 User Modeling and Personalization on Twitter 7
  • User Modeling Building Blocks 1. Temporal Constraints Francesca T Sport Schiavone 2. Profile Profile? Type concept weight Francesca Schiavone won ? # hashtag-based French Open #fo2010 entity-based T topic-basedFrenchOpen # fo2010 2. What type of concepts should represent interests? time June 27 July 4 July 11 User Modeling and Personalization on Twitter 8
  • User Modeling Building Blocks 1. Temporal Constraints Francesca (a) tweet-based Schiavone 2. Profile Profile? Type concept weight FrancescaFrancesca Schiavone won! Schiavone 3. Semantichttp://bit.ly/2f4t7a French Open Enrichment Tennis Francesca wins French Open French Thirty in womens Open (b) further enrichment tennis is primordially old, an age when agility and desire Tennis recedes as the 3. Further enrich the semantics of tweets? User Modeling and Personalization on Twitter 9
  • User Modeling Building Blocks 1. Temporal Constraints Profile? 2. Profile concept weight Type ?4. How to weight the Francesca Schiavone 4 3. Semantic concepts? French Open 3 Enrichment Tennis 6Concept frequency (TF) 4. WeightingTFxIDF Scheme weight(FrancescaTime-sensitive weight(French Open) weight(Tennis) Schiavone) time June 27 July 4 July 11 User Modeling and Personalization on Twitter 10
  • User Modeling Building Blocks 1. Temporal (a) time period Constraints (b) temporal patterns (a) hashtag-based (b) entity-based 2. Profile (c) topic-based Type 3. Semantic (a) tweet-based Enrichment (b) further enrichment (a) concept 4. Weighting frequency Scheme User Modeling and Personalization on Twitter 11
  • 1. Temporal (a) time period Constraints (b) temporal patterns (a) hashtag-based (b) entity-based 2. Profile (c) topic-based Type 3. Semantic (a) tweet-based Enrichment (b) further enrichment (a) concept 4. Weighting frequency SchemeAnalysisHow do the user modeling building blocks impact the (temporal)characteristics of Twitter-based user profiles? User Modeling and Personalization on Twitter 12
  • Dataset more than: 20,000 Twitter users 2 months Available online:10,000,000 tweets http://wis.ewi.tudelft.nl/umap2011/ Assange, WikiLeaks founder, Julian under arrest in London 75,000 news articles Nov 15 Dec 15 Jan 15 time User Modeling and Personalization on Twitter 13
  • ProfileSize of user profiles Type ~5% of the users entity-based do not make use of hashtags hashtag-based profiles are empty Entity-based user modeling succeeds topic-based for 100% of the hashtag-based users