Social Interaction Ontology

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Research report for social interaction ontology - including activity streams, online presence project, SIOC and FOAF.

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  • 트위터로 친구로 맺어진 분을 반갑게 여기서 뵙네요. 프레젠테이션 잘봤습니다
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Social Interaction Ontology

  1. 1. Research Draft Social Semantic Web and Social Interaction Ontology Seokchan (Channy) Yun Biomedical Knowledge Engineering Laboratory Seoul National University June 8th 2009
  2. 2. Agenda • Online Social Network – Traditional research • Social Semantic Web – FOAF/SIOC – Tripartite Social Ontology – Social Semantic Network • Activity-based Approach – Online Presence Project – Activity Streams • Social Interaction Ontology – Research Plan
  3. 3. Social Networks in Socialogy • Social Network used firstly J.A. Barnes (1954) • Research methodology in Social Sciences • Generally sameAs Network (Graph) Theory – Milgram’s six degrees of separation theory – Erdős number – Dunbar’s Number – 150 (average 124) – Diffusion of innovations
  4. 4. Representation of Social Network • Graph Model with Node and Edge
  5. 5. Emerging Online Social Network • New opportunities for social science – Explicit and implicit social network information – Large scale data sets – Dynamic data – Different modalities (profiles, email, IM, Twitter…) • Challenges – Theoretical – Friend on the Web = Friend in reality? – Extracting information – Heterogeneity – Quality of data – Time and space complexity – Ethical and legal challenges • Semantic technologies can help with some of the technical challenges
  6. 6. History • First Mover – Classmates.com, Match.com and sixdegree.com – Friendster and Orkut • Majority – Myspace and Facebook – Linkedin.com – Twitter.com
  7. 7. Classification
  8. 8. How succeed? • Allows a user to create and maintain an online network of close friends or business associates for social and professional reasons: – Friendships and relationships – Offline meetings – Curiosity about others – Business opportunities – Job hunting • Allows a user to share interests based on object-centered sociality with meaning – Sharing photo, video and bookmark – Life streaming over SNS – Broadcasting and publishing of my own content
  9. 9. Status of Online SNS John Breslin, The Social Semantic Web: An Introduction (2009)
  10. 10. Social Semantic Information Spaces
  11. 11. FOAF
  12. 12. Example of FOAF <foaf:Person> <foaf:name> Seokchan Yun </foaf:name> <foaf:mbox_sha1sum> 241021fb0e6289f92815fc210f9e9137262c252e </foaf:mbox_sha1sum> <foaf:homepage rdf:resource=quot;http://www.creation.netquot; /> <foaf:knows> <foaf:Person> <foaf:name>Hong-Gee Kim</foaf:name> <foaf:mbox rdf:resource=”mailto:hgkim@snu.ac.kr”/> <rdfs:seeAlso rdf:resource=“http://.../foaf.rdf /> </foaf:Person> </foaf:Person>
  13. 13. Common Structure
  14. 14. SIOC (John Breslin)
  15. 15. Example of SIOC <sioc:Post rdf:about=quot;http://koreacrunch.com/archive/firefox-supports-geolocation-servicequot;> <dcterms:title>Firefox supports Geolocation Service</dcterms:title> <dcterms:created>2006-09-07T09:33:30Z</dcterms:created> <sioc:has_container rdf:resource=quot;http://www.creation.net/?sioc_type=site#weblogquot;/> <sioc:has_creator> <sioc:User rdf:about=quot;http://www.creation.net/quot; rdfs:label=quot;Cloudquot;> </sioc:User> </sioc:has_creator> <sioc:content>Firefox 3.5 Beta 4 and higher starts to support W3C’s Geolocation APIs developed by Google.com based... </sioc:content> <sioc:topic rdfs:label=quot;Firefoxquot; rdf:resource=quot;http://koreacrunch.com/tags/firefox/quot;/> <sioc:topic rdfs:label=quot;Geolocationquot; rdf:resource=quot;http://koreacrunch.com/tags/...quot;/> <sioc:has_reply> <sioc:Post rdf:about=quot;http://koreacrunch.com/archive/351#comment-123928quot;> </sioc:Post> </sioc:has_reply> </sioc:Post>
  16. 16. FOAF+ SIOC 16
  17. 17. FOAF+SIOC+SKOS skos:isSubjectOf sioc:topic 17
  18. 18. Disconnected sites on the Social Web
  19. 19. Tripartite Social Ontology (Peter Mica) • A graph model of ontologies based on tripartite graphs of actors, concepts and instances – Actors: users – Concepts: tags – Instances: objects • Emergent semantics – General idea: observe semantics in the way agents interact (use concepts) • Bottom-up ontologies • Semantics = syntax + statistics
  20. 20. Dimensional Ontology Oci and Oac
  21. 21. e.g. Delicious • When looking at co-occurrence of terms (Oci ) – Network reflects language use – Better for clustering, determining ambiguity of terms and finding synonyms • E.g. travel - cote, provence, villa, azur, mas, holiday, vacation, tourism, france, heritage • When looking at community overlaps (Oac ) – Network reflects the domain – Better for finding broader/narrower terms, non-trivial relationships • E.g. google – gmail, picasa, youtube…
  22. 22. e.g. Flink
  23. 23. Social Semantic Network (Jason Jung)
  24. 24. Remained Question?
  25. 25. What’s Definition of Online Friends? http://answers.polldaddy.com/poll/1230119/?view=results Well-known Friends 9% Colleagues 7% Known Meet once in offline 25% Knowing only name 12% Famous person 3% Unknown FoaF 13% Unknown Everyone requested 32% Online Friend != Real FOAF’s knows is not knowing!
  26. 26. Twitter
  27. 27. Facebook
  28. 28. me2DAY
  29. 29. LinkedIn
  30. 30. Challenges • Discovering Knowledge Abdullah Al Reshood roommateOf Aafia Siddique Aafia Siddique isMemberOf Al Queda Aafia Siddique traveledTo Pakistan Mounir-al Motassad traveledTo Pakistan Abdullah Al Reshood isRelatedTo Al Queda ? Al Queda isRelatedTo Pakistan ? • Degree of User relationship – Coupling between users (high vs. weak) – Removing coupling bias in analysis
  31. 31. Online Presence Project (Milan Stankovic) • Feel of Presense – Status Messages – Online Status (Busy, Available, Away…) – Current listening music, activities…
  32. 32. Activity Streams (Chris Messina) • Lightweight simple Atom based syndication for user’s activities • Widely supported by Facebook, MySpace etc. • Basic Format – User, Verb, Noun
  33. 33. Example of Activity Streams <entry> <id>tag:photopanic.example.com,2008:activity01</id> <title>Geraldine posted a Photo on PhotoPanic</title> <published>2008-11-02T15:29:00Z</published> <link rel=quot;alternatequot; type=quot;text/html“ href=quot;/geraldine/activities/1quot; /> <activity:verb> http://activitystrea.ms/schema/1.0/post </activity:verb> <activity:object> <id>tag:photopanic.example.com,2008:photo01</id> <title>My Cat</title> <published>2008-11-02T15:29:00Z</published> <link rel=quot;alternatequot; type=quot;text/html“ href=quot;/geraldine/photos/1quot; /> <activity:object-type> tag:atomactivity.example.com,2008:photo </activity:object-type> <source> <title>Geraldine's Photos</title> <link rel=quot;selfquot; type=quot;application/atom+xml“ href=quot;/geraldine/photofeed.xmlquot; /> <link rel=quot;alternatequot; type=quot;text/html“ href=quot;/geraldine/quot; /> </source> </activity:object> <content type=quot;htmlquot;> &lt;p&gt;Geraldine posted a Photo on PhotoPanic&lt;/p&gt; &lt;img src=quot;/geraldine/photo1.jpgquot;&gt; </content> </entry>
  34. 34. Other approaches
  35. 35. Questions • Twitter – There are many spammers and followers. – Whom I should follow? Who is expert? • me2DAY – There are many friends – Who disconnected in my friendship? • Flickr – There are many photos. – What’s good photos enjoying with friend? • RateMDs – There are many doctors. – What’s good doctors recommended by friends?
  36. 36. Answers • 1. Measuring degree of user relationship – Twitter: Following < RT < Reply < Direct Message < SMS – me2Day: me2 < Link < Reply < Memo < Gift < SMS – Exporting Social Interaction Ontology • 2. Modeling of user degree – Similarity formula (A,B) • 3. Integration data for answer
  37. 37. Pre-work for solving problem • Social web evolves direct sharing and broadcasting instead of document link based distribution and knowledge discovering. – Social Interaction is more important in social networks. – FriendFeed, Facebook life streaming, Twitter • Need to represent “Degree between people” – Writing simple ontology represents interaction • Channy replies Hong-Gee (What) (When) in Facebook • John retweets Channy (What) (When) in Twitter
  38. 38. Why new ontology? • SIOC – Only focusing on relationship with site(forum), contents and person. • OPO – Only focusing “Presence” not to be interested in “Activity” – No description on various interaction such as Twitter’s RT – Need to more practical • Activity streams – Atom (RDF) based – Only description for Person / Verb / Object
  39. 39. Twitter interaction
  40. 40. Facebook interaction
  41. 41. me2DAY interaction
  42. 42. Social Interaction Ontology • Focusing on User-to-User – User / Verb / User in Sites select count(?y) as ?cdegree { • E.g. fromAccount Act toAccount { ?y interAct:retweet ?x} UNION {?x interAct:directmessage ?y} • Connection with FOAF and SIOC } group by ?x – foaf:Person – foaf:holdsAccount • sioc:User rdfs:subClassOf foaf:onlineAccount – interAct:fromAccount rdfs:sioc:User • Expression for various interaction – Verb : comment, reply, me2, RT, hashtag… • E.g act:comment sioc:Sites
  43. 43. Research Plan • Who disconnected in my friendship on me2DAY? – Modeling Social Interactive Ontology – Export me2DAY activity to SIO – Measuring coupling-degree index • Distance = # of interaction/ time interval • Priority = normalized value for each interactions – Evaluation with user’s reaction for alert • Whom I should follow? Who is expert in Twitter? – Export twitter activity to SIO – Measuring coupling-degree index – Evaluation with user’s reaction for recommendation
  44. 44. Interaction Interaction Interaction Ontology Ontology Ontology Exporter Exporter Exporter
  45. 45. Q&A channy@snu.ac.kr http://www.creation.net Twitter: @channyun

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