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Personalized Filtering of Twitter Stream

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With the rapid growth in users on social networks, there is a corresponding increase in user-generated content, in turn resulting in information overload. On Twitter, for example, users tend to receive un- interested information due to their non-overlapping interests from the people whom they follow. In this paper we present a Semantic Web ap- proach to filter public tweets matching interests from personalized user profiles. Our approach includes automatic generation of multi-domain and personalized user profiles, filtering Twitter stream based on the gen- erated profiles and delivering them in real-time. Given that users inter- ests and personalization needs change with time, we also discuss how our application can adapt with these changes.

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Personalized Filtering of Twitter Stream

  1. 1. Personalized Filtering of the Twitter Stream Pavan Kapanipathi 1,2, Fabrizio Orlandi1, Amit Sheth2 ,Alexandre Passant 11 Digital Enterprise Research Institute, Galway – Ireland 2 Kno.e.sis, Dayton, OH- USA 1
  2. 2. Motivation Twitter – Growth Information Overload 2
  3. 3. Motivation• How many people should I follow ?• Am I receiving latest/complete information ? 3
  4. 4. Background Twarql – Streaming annotated tweets  Semantic Web Technologies  Annotate Tweets (DBpedia Entities)  Filter Stream using SPARQL Queries formulated  Example:  Stream all the tweets related to Semantic Web generated in Germany ?tweet moat:taggedWith ?topic . ?topic dcterms:subject category:Semantic_Web . ?tweet sioc:has_creator ?user . ?user geonames:locatedIn dbpedia:Germany . 4
  5. 5. Approach -- Overview The new iPhone has a Broadcast3.5-inch screen, Football released today User Profiles Filter Apple 5
  6. 6. Annotate: iPhone Get ?user foaf:interest Subscribers The newiPhone has a 3.5- inch screen, Architecture dbPedia:iPhone Union based on preference ?user foaf:interest released today Category:Apple Get Interested Subscribers RDF Semantic Filter Notify Update A N RDF N Store and O T Query Topics Semantic Hub A Fetch Updates T RS O R S Store FOAF Update RSS Profile Generator Push Updates to Interested Users Create Profile 6
  7. 7. Contribution Profile Generator  Automatic generation of User Profiles Semantic Filter  Annotating Twitter Stream with concepts from Linked Open Data Semantic Hub  Delivering tweets to appropriate Interested Users (near real-time) 7
  8. 8. Profile Generator Get Interested Subscribers RDF Semantic Filter Notify UpdateAN RDFN Store andOT Query Topics Semantic HubA Fetch UpdatesT RSOR S Store FOAF Update RSS Profile Generator Create Profile 8
  9. 9. Profile Generator DisconnectedSocial websites Isolated data silos Social Networking Sites as Walled Gardens by David Simonds (Used with permission) 9
  10. 10. Interlink social websites Integration & Merge and model user data User Modelling User Profile Personalise users’ experience using their profileRecommendations Adaptive Systems Search Personalisation 10
  11. 11. Profile Generator Data Extraction  Twitter, Facebook, LinkedIn  Example: Tweets, FB Likes Profile Generation  Interests extracted from collected data  Entity spotting (user generated data)  Explicit interests specified by user (Facebook likes etc)  Weighted Interests Semantic Representation of Profiles  FOAF profile 11
  12. 12. Semantic Filter Get Interested Subscribers RDF Semantic Filter Notify UpdateAN RDFN Store andOT Query Topics Semantic HubA Fetch UpdatesT RSOR S Store FOAF Update RSS Profile Generator Create Profile 12
  13. 13. Semantic Filter Twitter Streaming API Microblog Metadata  Twitter provides metadata  Author, date, location etc..  Metadata Extracted  DBPedia Entities, URLs Generate SPARQL Query representing interested Users  Retrieved at Semantic Hub 13
  14. 14. Semantic Filter – RDF<> rdf:type sioct:MicroblogPost ; sioc:content "P Groth and Y Gil, Linked Data for Network Science #iswc2011 #lisc2011 #linkeddata-“• sioc:has_creator <> ; foaf:maker <> ; moat:taggedWith dbpedia:Linked_Data ; moat:taggedWith dbpedia:Network_Science ;<> rdf:type opo:OnlinePresence ; opo:startTime •2010-03-20T17:55:42+00:00 ; opo:customMessage <> .<> geonames:locatedIn Dbpedia:Ohio .[...] 14
  15. 15. Semantic Filter– SPARQL Query Generate SPARQL Queries  Representing FOAF of interested users SELECT ?user WHERE { { ?user foaf:interest dbpedia:Linked_Data .} UNION { ?user foaf:interest dbpedia:Network_Science .} } 15
  16. 16. Semantic Hub Get Interested Subscribers RDF Semantic Filter Notify UpdateAN RDFN Store andOT Query Topics Semantic HubA Fetch UpdatesT RSOR S Store FOAF Update RSS Profile Generator Create Profile 16
  17. 17. PubSubHubbub Protocol  PubSubHubbub is an extension to RSS/Atom  Open, web hook based, pubsub protocol for Real-time notification of updates Drawback  Publisher has no control over the dissemination of his content Extension – Semantic Hub  Publisher controlled dissemination  SPARQL Query representing the subset of target subscribers 17
  18. 18. PubSubHubbub Protocol ExtensionHey I have new Here is the Give me new contentcontent for feed the new X + my of feed X content Sub - A preference Y Sub - B Pub Semantic Hub Sub - C Here it Sub - D is Get the subscribers Social of Pub whose profile Graph matches preference Y 18
  19. 19. Semantic Hub RSS Extension  Preference – to include the sparql queries Push content  FOAF profiles of the subscribers are matched with the preference  Interested subscribers receive the content Accepted as a full paper in the In-Use track at ISWC 2011 19
  20. 20. Conclusion Single consistent profile rather than profiles on multiple social networks  User Profile Generation Architecture for Personalization of twitter stream  Reduce load on users to follow others  Public tweets streamed  Access to information from experts in domains  Are you following experts in your domain of interest?  Experts public tweets will be streamed Dynamic groups of users  Interest Driven 20
  21. 21. Future work -- Why RDF Twarql features  Concept feeds as interests of the users
  22. 22. Future Work Periodic FOAF profile generation for users  Twitter Stream reflecting the changing interests Extending to other social networks (G+, FB) 22
  23. 23. Thanks Contact us on Twitter  @pavankaps @badmotorf @terraces @amit_pEmail: {pavan, amit} {fabrizio.orlandi, alexandre.passant}@deri.orgThis work is funded by (1) Science Foundation Ireland under grant number SFI/08/CE/I1380 (Lıon 2) and by anIRCSET scholarship supported by Cisco Systems (2) Social Media Enhanced Organizational Sensemaking inEmergency Response, National Science Foundation under award IIS-1111182, 09/01/2011 - 08/31/2014. 23
  24. 24. 24
  25. 25. Architecture 25
  26. 26. Agenda Motivation Contribution Architecture Conclusion Future Work 26
  27. 27.  Weighing function based on RTs and other active engagements of the user 27