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@twitter Mining #Microblogs Using #Semantic Technologies

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Presenation of Selver Softic at 6th Workshop on Semantic Web Applications and Perspectives (SWAP 2010)

Presenation of Selver Softic at 6th Workshop on Semantic Web Applications and Perspectives (SWAP 2010)

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  • 1. @twitter Mining #MicroblogsUsing #SemanticTechnologies
    Selver Softic, Martin Ebner, Herbert Mühlburger , Thomas Altmann, Behnam Taraghi
  • 2. Web 2.0 - well knownstory
    Web 2.0 technologiesbroughtuserscloserto Web …
    Wikis, Blogs, Forums …
    Podcasts, RSS, XML …
    … thenusersstarted
    togeneratecontent …
    Source: http:mediabistro.com
  • 3. From Web toSocial Web
    Result = a vastofinformation
    Text, Pictures, Audio, Videos ….
    Communication, networking, exchangeofdata
    Web becamemore personal
    Cultural, geographicalandsocialbordersdisappeared
    Source: http://www.ignitesocialmedia.com
  • 4. Social Media Boom!
  • 5.
  • 6. Socialsitesaredatasilos
    source: www.pidgintech.com
  • 7. But still disconnected ?
    source: www.pidgintech.com
  • 8. Data is still captured in Walled Garden!
  • 9. Statements
    Social Web relies on usersandcommunicationamongthem
    Whilecommunicatingusersproduceorconsumecontent
    Socialsitesaredatasilosrich on varietyofinformation
    Thisinformationcouldbeinterestingfor:
    monitoring of trends, advertising, statistics, reputation, news broadcasting , tagging …
    Thisdataiscaptured in Walledgarden !!!
  • 10. Questions
    Howtousethisdatatogainmoreusefulinsights
    Whataretheadvantagesof online (offline) search on such dataandhowtoreachit in an uniform way
    Is itpossibletostructurize, connectandexposethedata in order tobeusedbyhumansandmachinesmoreefficiently
    Whatwould an architecturelooklikeforthisissue
  • 11. Social Web Trends
    Microblogging
    SocialBookmarking
    Social Networking
    Social Marketing
    Sharing Photos, Videos …
    Source: http://socialwebresearch.com
  • 12. Microblogs
    Microblogs
    Usedforcommunication,publishingandinformationexchange
    Simple forprocessing
    Information generatedbymany different users
    Socialuserrelations
    Tripartitecommunicationstructure
    Varietyofinformations
    Noboundariesbyculture,locationortechnology (mobile users)
    Twitter
    Most Popular
    Large amountoddata
    But limited
    According: http://an.kaist.ac.kr/traces/WWW2010.html
    41.7 million user profiles, 1.47 billion social relations, 4,262 trending topics, and 106 million tweets
  • 13. SemanticaspectsandTwitter
    Twitter
    User realtions
    Tweetsasshortinformationartefacts
    Communication withtripartitepattern
    Time relatedinformation
    Vocabularies
    SIOC, FOAF, Dublin Core
  • 14. Linked Data andTwitter
    Twittercontainsinfos on:
    People, Organisations, Locations, Trends …
    LOD Cloudcontains
    Billionsoftriplesabout:
    Geolocations , dataaboutscience, government, commonknowledge, persons, news …
    Vocabularies
    MOAT, CommmonTag
  • 15. Architecture model
  • 16. Acquisition - Grabeeter
  • 17. Grabeeter
    Search in your Tweets
    Filter your Tweets by date
    Search in your Tweets offline using the Grabeeter Client
    Filter your tweets offline using the Grabeeter Client
    Grabeeter provides an API
  • 18. Triplification Module
    Author
    Date
    Content
    Reciever
    <tweet url="http://grabeeter.tugraz.at/tweet/199272" text="Sitting in Prater #vienna, launch party. Nice" screen_name="selvers" created="2010-08-19" twitterUrl="http://twitter.com/selvers/status/21606926237"/>
    RDF
    Store
    Triplifier
  • 19. Triplification Module
    @prefix foaf: <http://xmlns.com/foaf/0.1/> .
    @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
    @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
    @prefix sioc: <http://rdfs.org/sioc/ns#> .
    @prefix sioct: <http://rdfs.org/sioc/types#> .
    @prefix dcterms: <http://purl.org/dc/terms/#> .
    <http://twitter.com/selvers/status/21606926237> rdf:typesioct:MicroblogPost ;
    sioc:content "Sitting in Prater #vienna, launch party. Nice" ;
    sioc:has_creator <http://twitter.com/selvers/> ;
    foaf:maker <http://grabeteer.tugraz.at/foaf/selvers/> ;
    dcterms:created “2010-08-19” ;
    rdfs:sameAs <http://grabeeter.tugraz.at/tweet/199272> .
    <http://twitter.com/selvers/> rdf:typefoaf:Person ;
    foaf:name "SelverSoftic" ;
    foaf:depiction <http://a0.twimg.com/profile_images/905118560/f9e4b6eba.13070201_3_normal.jpg> ;
    foaf:knows <http://twitter.com/hmuehlburger/> ;
    foaf:knows <http://twitter.com/mhausenblas/> ;
    foaf:knows <http://twitter.com/mebner/> .

  • 20. Interlinking Module
    Hashtags (People, Organisation, Locations)
    MOAT, CommonTag
    Later NLP processedcontent, SILK Framework
    SELECT ?post ?content ?maker ?name
    WHERE {
    ?post rdf:typesioct:MicroblogPost;
    foaf:maker ?maker;
    ?makerfoaf:name ?name;
    sioc:content ?content.
    FILTER(regex(?content,#vienna))
    }
    Classifier
    tag: tagName "vienna" ;
    moat: tagMeaning
    <http://dbpedia .org/resource/Vienna>
    tag: taggedResource <http://twitter.com/selvers/status/2160692623>
  • 21. Analysis
  • 22. Conclusions & Outlook
    Currentstateofthearttechnologiessufficetorealisetheproposedarchitectureparadigm
    Interlinkingwith LOD Cloud (Tweet-O-Sphere)
    Involving NLP Methods
    Sentiment classification
    (Re)TaggingofTweets
    Providing SPARQL Endpoint + Lookup Serviceasresearchinterface
    SocialSemantic Web Apps
  • 23. Questions?