Using Hyperlinks to Enrich Message Board Content with Linked Data
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Using Hyperlinks to Enrich Message Board Content with Linked Data

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Presentation from I-SEMANTICS 2010, Graz, Austria. Based on the paper "Using Hyperlinks to Enrich Message Board Content with Linked Data" by Sheila Kinsella, Alexandre Passant, and John G. Breslin.

Presentation from I-SEMANTICS 2010, Graz, Austria. Based on the paper "Using Hyperlinks to Enrich Message Board Content with Linked Data" by Sheila Kinsella, Alexandre Passant, and John G. Breslin.

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Using Hyperlinks to Enrich Message Board Content with Linked Data Using Hyperlinks to Enrich Message Board Content with Linked Data Presentation Transcript

  • Using Hyperlinks to Enrich Message Board Content with Linked Data Sheila Kinsella, Alexandre Passant, John G. Breslin Chapter
  • Introduction
    • Hyperlinks are an important part of online conversation, often represent identifiable concepts
    • More and more often these hyperlinks have corresponding structured data sources
    • Our aims in this study
      • Study the growth of structured, user-generated data and links in social media over 10 years
      • Investigate how we can use this data for enhanced analysis of online conversation
  • Example post
    • imdb:tt0211915 foaf:topic dbpedia:Amélie .
    • dbpedia:Amélie dc:title "Amélie“ .
    • dbpedia:Amélie dc:date "2001" .
    • dbpedia:Amélie dbpprop:starring dbpedia:Audrey_Tautou .
    • dbpedia:Amélie dbpprop:director dbpedia:Jean-Pierre_Jeunet .
    http://www.imdb.com/title/tt0211915/ = Identifier we can use to query LinkedMDB/Dbpedia/Freebase…
  • Dataset enrichment of XYZ
  • Boards.ie SIOC Data Competition
    • 2008 competition to do something interesting with message board data
    • February 1998 – February 2008
    • SIOC, FOAF, DC
    • ~ 130k users
    • > 7m posts
  • Change in type of websites linked to of XYZ 2002/2003 2007/2008 Domain Main Content Type bbc.co.uk news media komplett.ie shop ireland.com news media eircom.net Web hosting yahoo.com news/discussion r te.ie news media google.com Web search g eocities.com Web hosting iol.ie Web hosting microsoft.com technical support Domain Main Content Type youtube.com UGC: video-sharing wikipedia.org UGC: encyclopedia komplett.ie shop myspace.com UGC: SNS/music flickr.com UGC: photo-sharing bbc.co.uk news media rte.ie news media carzone.ie shop photobucket.com UGC: media hosting ebay.ie shop
  • Identification of external data sources
    • youtube.com
    • wikipedia.org (dbpedia)
    • komplett.ie
    • bbc.co.uk
    • myspace.com (dbtunes)
    • rte.ie
    • carzone.ie
    • google.com
    • photobucket.com
    • flickr.com
    • microsoft.com
    • eircom.net
    • ebay.ie
    • imageshack.us
    • imdb.com (linkedmdb)
    • ebay.co.uk
    • yahoo.com
    • amazon.co.uk
    • google.ie
    • blogspot.com
  • Data sources
  • Structured Data
    • RDF Data
      • Rich descriptions of resources using common ontologies
      • Linked Data, RDFa, SPARQL endpoint, RDF dumps
      • E.g. <X> <foaf:topic> <dbpedia:Education> .
      • We store this data and merge equivalent URIs if required
    • API Data (fixed values)
      • Less rich, heterogeneous, lacking common semantics
      • Often available as JSON/XML, easily converted to RDF
      • E.g. <category term='Education'/>
      • We manually mapped these to URIs
    • API Data (tags)
      • Plain text annotations, meaning can be ambiguous
      • E.g. “ education ”
      • We performed a naïve mapping of tags to URIs
    EXPRESSIVENESS
  • Analysis of external links For 2007/2008, we could access structured data for over 9% of all posted links 98/ 99/ 00/ 01/ 02/ 03/ 04/ 05/ 06/ 07/ 99 00 01 02 03 04 05 06 07 08
  • The enriched dataset DBPEDIA SIOC Linked Data/ Web APIs (30k links, 21k unique) concepts 24,000 RDF RDF RDF RDF 3,000 500 1,500 8,000 6,000 2,000 6,000 23,000
  • Analyis example: Post content % of posts containing name/title
  • Analyis example: Content sharing % of content age
  • Analysis example: User profiling
  • Analysis example: User profiling
  • Conclusions
    • Many links posted in social media sites correspond to a structured data source
      • In 2007/2008 already more than 9%
    • This data can enable us to carry out new analysis and get new insight into online communities
    • Also potential for new applications e.g. content recommendation, enhanced cross-site browsing
    • Current work: using external structured data for improving topic identification in online communities