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Semantic Enrichment of Twitter Posts for User Profile Construction on the Social Web
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Semantic Enrichment of Twitter Posts for User Profile Construction on the Social Web

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  • 1. Semantic Enrichment of TwitterPosts for User ProfileConstruction on the Social Web Fabian Abel, Qi Gao, Geert-Jan Houben, Ke Tao {f.abel, q.gao, g.j.p.m.houben, k.tao}@tudelft.nl Web Information Systems Delft University of Technology Delft University of Technology
  • 2. Problems of today’s Web Systems Hi, I’m your new user. Give me personalization! System A profileSystem B Hi, I have a ? new-user problem! profile profileSystem C Hi, I’m back and I have new interests. profile How can we tackle these problems? System D Hi, I don’t know your time profile current demands! Semantic Enrichment of Twitter Posts for User Profile Construction 2
  • 3. What we do: news personalized E-learning recommendation search User modeling with rich semantics Analysis and User interested in: Modeling people topics events … Linking microblog posts & external resources Linkage, Semantic Enrichment Semantic Enrichment -  topic detection -  entity recognition & identification user data Microblogging Semantic Enrichment of Twitter Posts for User Profile Construction 3
  • 4. Research Questions User A Francesca Schiavone is sportsman of the year #sport #tennis •  Twi%er  posts  (Tweets)   •  short:  up  to  140  characters   SI Sportsman of the year: Surprise French Open •  Including  various  topics   champ Francesca Schiavone User B @hillhulse In an era where Thirty in womens tennis is power players rule, I am primordially old, an age when happy that francesca agility and desire recedes as the next wave of younger/ schiavone is becoming•  -­‐>Ques%on1:  Can  we  provide  meaningful faster/stronger players sport idol of the year! encroaches. Its uncommon for  user  profiles  from  Twi%er  acCviCes?   any athlete to have a breakthrough season at 30, but its exceedingly… news article User C•  -­‐>Ques%on2:   Can   we   re-­‐use   the   Tiw%er nice! http://bit.ly/eiU33c -­‐based   profiles   for   other   applicaCon,   such  as  personalized  recommendaCon?   Semantic Enrichment of Twitter Posts for User Profile Construction 4
  • 5. SI Sportsman of the year: Surprise French user Open champ Francesca Schiavone@hillhulse In an era where power Thirty in womens tennis is primordiallyplayers rule, I am happy that old, an age when agility and desirefrancesca is becoming #sport recedes as the next wave of younger/idol of the year! faster/stronger players encroaches… microblog post news article linkage oc:SportsGameenrichment enrichment topic:Tennis event:FrenchOpen topic:Sports topic:Sports person:Francesca_Schiavone user modeling Profile Topics of interest: - topic:Tennis - topic:Sports People of interest: - person:Francesca_Schiavone Events of interest: - event:FrenchOpen Semantic Enrichment of Twitter Posts for User Profile Construction 5
  • 6. news E-learning Public datarecommendation Analysis and User Modeling Linkage, Semantic Enrichment user data Microblogging Semantic Enrichment of Twitter Posts for User Profile Construction 6
  • 7. Linkage Semantic Enrichment of Twitter Posts for User Profile Construction 7
  • 8. Linkage Discovery•  Content-based •  using all of the words to as an search query and apply TF*IDF to rank the news articles•  Hashtag-based •  using hashtag(s) to search the related news articles•  URL-based – whether a Twitter message contain news-related URL(s) •  URL-based (Strict): only consider content of the Twitter message •  URL-based (Lenient): also consider reply or re-tweet messages•  Entity-based •  using entity(s) to search the related news articles•  Temporal constrain (for content-, hashtag-, and entity-based) •  Tweets and news articles should be published in a certain time span Semantic Enrichment of Twitter Posts for User Profile Construction 8
  • 9. Linkage Discovery SI Sportsman of the year: Surprise French Open champ Francesca Schiavone nice! http://bit.ly/eiU33c URL-based Thirty in womens tennis is primordially old, an age when agility and desire recedes as the next wave of younger/faster/ stronger players encroaches. Its uncommon for any athlete to have a breakthrough season at 30, but its exceedingly… news article URL d -b ase E n tity Olympic champion and world Francesca Schiavone is number nine Elena Dementieva announced her sportsman of the year retirement #sport #tennis TemponE ral y-b tit coas The 29-year-old Russian delivered nstd ain er the shock news after losing to Francesca Schiavone in the group publish date stages of the season-ending Old news  tournamen … news article publish date Semantic Enrichment of Twitter Posts for User Profile Construction 9
  • 10. Analysis and Evaluation on Linkage Discovery andSemantic Enrichment•  Evaluation on the performance of the strategies for linkage•  Analysis on the impact of linkage discovery on semantic enrichment of Twitter posts ITEM VALUE Crawling time three weeks Users 48,927 Tweets > 2m News Media / News More than 60/ 77,544 Semantic Enrichment of Twitter Posts for User Profile Construction 10
  • 11. Dataset - overview•  a power-law-like distribution for the number of tweets per user•  c.a. 500 users were highly active during the observation period Semantic Enrichment of Twitter Posts for User Profile Construction 11
  • 12. Evaluation on Linkage Discovery JKL234516%750<DI0=% !"*!(,%•  1427 tweet-news pairs were randomly selected JKL234516%7H1/D1/0=% !")*+% @/A0B234516% !")#$$%•  Human experts rate the relations with a scale @/A0B234516%7CD0?.E0%01FG.<4H%I./50<4D/05=% between 1 (“not related”) and 4 (“perfected !"&()% match”) >45?049234516% !"&!$% -./01/0234516%78492.:2;.<65=% !"#!#$% !% !"#% !"% !"$% !"&% !"(% !"+% !")% !"*% !",% !"#$%&%() Semantic Enrichment of Twitter Posts for User Profile Construction 12
  • 13. Analysis on Linkage Discovery and Semantic Enrichment•  URL-based strategy: more than 10 tweet-news relations for c.a. more than 1000•  Entity-based strategy: found a far more higher number of tweet-news relations•  Hashtag-based strategy failed for more than 79% of the users because of the limited usage of hashtags•  Combined all strategy: higher than 10 tweet -news relation found for more than 20% of the users Semantic Enrichment of Twitter Posts for User Profile Construction 13
  • 14. news E-learning Public datarecommendation Analysis and User Modeling Linkage, Semantic Enrichment user data Microblogging Semantic Enrichment of Twitter Posts for User Profile Construction 14
  • 15. User Profile Construction event:FrenchOpen topic:Tennis User modeling with rich semantics: interested in: linkage people topics events … user profile construction #sport temporal Profile types enrichment constrainsperson:Francesca_Schiavone • hashtag- • tweet-only • specific time based • exploitation of period • topic-based external news • temporal pattern • entity-based resources • No constrains topic:Sports time weekday weekend Semantic Enrichment of Twitter Posts for User Profile Construction 15
  • 16. Analysis of Profile Characteristics Entity-based profiles Topic-based profiles 10000 News-based News-based Tweet-based distinct topics per user profile Tweet-basedentities per user profile 1000 10 100 10 0 0 1 10 100 1000 1 10 100 1000 user profiles user profiles By exploiting the linkage between tweets and news articles, we get more distinct entities / topics (semantics)! Semantic Enrichment of Twitter Posts for User Profile Construction 16
  • 17. Analysis of Profile Characteristics number of hashtags per user profile 10000 entity-based (news) hashtag-based 1000 100 10 1 1 10 100 1000 user profilesBy extracting semantics from tweets and news articles, we getricher user profiles! Semantic Enrichment of Twitter Posts for User Profile Construction 17
  • 18. Recommender Experiment •  Personalized news recommendation – recommending new articles that fit into user’s interests[1]semantic enrichment improves the Exploiting linkage improves the qualityquality of recommendation of recommendation.[1] Fabian Abel, Qi Gao, Geert-Jan Houben, Ke Tao. Analyzing User Modeling on Twitter for Personalized News Recommendations. In Proceedings of International Conference on User Modeling, Adaptation and Personalization (UMAP), Girona, Spain, Springer, 2011 Semantic Enrichment of Twitter Posts for User Profile Construction 18
  • 19. Conclusions and Future Work•  Twitter-based user modeling framework •  exploiting linkage between tweets and external news resources •  extract semantics from content of both tweets and news resources •  various design dimensions for user profile construction•  Evaluation and analysis on linkage discovery •  good performance with respect to precision and coverage•  Evaluation Analysis on user profile construction •  Richer (semantic!) user profiles •  constructed profiles for external application - improved accuracy of news recommendations with enriched user profiles•  Future work •  Temporal dynamic of Twitter-based user profiles and its impact on personalization Semantic Enrichment of Twitter Posts for User Profile Construction 19
  • 20. Thank You! q.gao@tudelft.nl Twitter: @qigaoshQi Gao http://wis.ewi.tudelft.nl/tweetum/Semantic Enrichment of Twitter Posts for User Profile Construction 20

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