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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  • How can both of these be done at one – Personalizing your twitter streamPut the name of the author of the source
  • Friends, industry experts and favourite celebrities
  • User generated content from the social networks (not profiles from the social network wont include the social graph)----- Meeting Notes (10/19/11 15:25) -----Rather than SPARQL syntax -- Generic (Make sure that the keywords are highlighted)
  • ----- Meeting Notes (10/19/11 15:25) -----Rather than profile genrator (Aggregating profile information)----- Meeting Notes (10/19/11 15:27) -----Before contributions give some background
  • User generated content from the social networks (not profiles from the social network wont include the social graph)----- Meeting Notes (10/19/11 15:25) -----Rather than SPARQL syntax -- Generic (Make sure that the keywords are highlighted)
  • ----- Meeting Notes (10/19/11 15:25) -----1. Emphasize on Filtering2. Twarql enabled data
  • User generated content from the social networks (not profiles from the social network wont include the social graph)----- Meeting Notes (10/19/11 15:25) -----Rather than SPARQL syntax -- Generic (Make sure that the keywords are highlighted)
  • Highlight when speaking about the particulars
  • User generated content from the social networks (not profiles from the social network wont include the social graph)----- Meeting Notes (10/19/11 15:25) -----Rather than SPARQL syntax -- Generic (Make sure that the keywords are highlighted)
  • Merge advantages and conclusion slide
  • Alex Blog post about.We use the semantic web technologies like RDF and SPARQL to filter the data. The information in the tweets is extracted and then the RDF triples are generated for each tweet. SPARQL queries are used to query these triples.For example. A sprarql Query which queries for all the tweets which has entities related to the dbPedia:HelathCare is subscribed. Our system filters the incoming data with this query and outputs the tweets.Pu
  • 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 Overloadhttp://www.cmswire.com/cms/customer-experience/35-key-twitter-statistics-infographic-012384.php 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<http://twitter.com/rob/statuses/123456789> rdf:type sioct:MicroblogPost ; sioc:content "P Groth and Y Gil, Linked Data for Network Sciencehttp://bit.ly/owxcJg #iswc2011 #lisc2011 #linkeddata-“• sioc:has_creator <http://twitter.com/rob> ; foaf:maker <http://example.org/rob> ; moat:taggedWith dbpedia:Linked_Data ; moat:taggedWith dbpedia:Network_Science ;<http://twitter.com/rob/statuses/123456789#presence> rdf:type opo:OnlinePresence ; opo:startTime •2010-03-20T17:55:42+00:00 ; opo:customMessage <http://twitter.com/rob/statuses/123456789> .<http://twitter.com/rob> 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}@knoesis.org {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

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