Social Semantic Web Paper Summaries 2: Social Semantic Web by John G. Breslin


In 2018, I have taken a master’s course from Bogazici University, called Social Semantic Web (CMPE 58H), teached by Suzan Üsküdarlı. (

I have wrote summaries for a few papers there. Today, I have decided to share them with you. This is both to share my understanding on these papers and to show my approach on how to read papers. Summary of the second paper is below.


2018 yılında Boğaziçi Üniversitesinde Sosyal Semantik Web (CMPE 58H) diye bir ders almıştım, Suzan Üsküdarlı hocamız dersi veriyordu.(

O derste birkaç makale özeti yazdım. Şimdi, o özetleri paylaşmaya karar verdim. Bunu, hem bu makalelere bakış açımı yansıtsın, ilgililer varsa okusun diye yapıyorum, hem de kendi makale okuyuş yöntemimi paylaşmak için yapıyorum. İkinci makalenin özeti aşağıda.


Social Semantic Web


John G. Breslin

About Author:

John G. Breslin: He founded SIOC while he was working in DERI. He also has other works such as co-founding StreamGlider and founding New Tech Post.


The article presents us the Social Semantic Web and speaks of Web 2.0 which made Social Web a possible thing, in the first part (12.1). Then he categorizes the examples of Social Semantic Web and tells about those (12.2). In the last section, he talks about advanced matters about Social Semantic Web.


12.1.1 The Social Web

a-The reasons why implementing Semantic Web on Social Web could be useful:

  • Interoperatibility between websites.
  • New ways to represent and transfer content within and across websites.

b-Basic Unique Features of Web 2.0:

  • Community: Users can add, change content.
  • Mashups: Several services can be used in a site (APIs)
  • AJAX: Foundation of the other two,responsive interfaces. Asynchronous communication.

Web 2.0 Uses users’ collaboration

Social Web: These are the web interactions that are social, participatory

Social Webs are also used in intranets, however this is not as succesful as the implementation on the Internet.

12.1.2 Issues with The Social Web

  • Social Webs are independent data silos. They cannot interoperate with each other. Tranfering a profile is not possible.

The reason this fact suits Social Web’s book is that they can lock their users in. Users are not mobile across different social webs.

  • Second (technical) reason is there are no conventional methods to transfer information between sites.

RSS is a good shot however is not enough. Transfering data across social websites is hard .

12.1.3 Bridging Social Web and Semantic Web

Some vocabularies that are succesful:

  • RSS (Really Simple Syndication , RDF Site Syndication)
  • FOAF (Friend of a friend)
  • SIOC (Semantically Interlinked Online Communities)

Semantic web makes data interchange and interoperation between applications possible.

When you apply Semantic Web on Social Web, Semantic Social Web emerges. This is a network of interlinked and semantically rich knowledge.

Two (plus one) ways to integrate Semantic Web and Social Web:

  • Using Semantic Web tecchnologies to model social data.
  • Taking advantage of user’s activity in Web 2.0
  • Using Social Web to provide metadata.

Combination of Social Web and Semantic Web can be more than the sum of its parts. The data of Social Web can benefit Semantic Web, Semantic Web’s conventional methods can benefit Social Web.

Possible good that Social Semantic Web will bring:

  • Easier information obtaining
  • Gathering profiles from many websites into one place.
  • Using web as a clipboard to drag pre-made information when needed.
  • No need to make repeated statements across various websites.
  • New ways to create intelligent user interfaces will emerge based on semantic information that is provided by users (about their interests etc.)
  • Mashups
  • Detailed queries
  • Emergent Semantics may be used to gather more information from content or metadata.

12.1.4 Ontologies (Syntaxes of represantation) for Social Web

  • FOAF (foaf:knows is used a lot)
  • SIOC (Interlinking online communities such as blogs, message boards etc.) (Gained attention, can also be used in other cases than online communities, such as business enviroments. High level concepts in SIOC makes this possible.)
  • SKOS (Simple Knowledge Organization System)
  • hCard (Electronic Business Cards)
  • XFN (XHTML Friends Network) (more detailed relationships than FOAF)

Ontologies for Semantic Tagging:

  • Tag Ontology: First one.
  • The Social Semantic Cloud of Tags (SCOT):Able to transfer not only the content but also the tags and tagging actions.
  • Meaning of A Tag (MOAT): Can link tags to external entities such as wiki pages. This provides a meaning to those parts. MOAT is not a single model, it also brings a framework.
  • Others: WIF, WAF, SAM, NABU, mle, SWAML, OPO, APML

12.2 Example Applications

12.2.1 Semantic Blogging

Some tagging services to categorize blogs exist however, advanced queies on blogging cannot be done.

The goal is:

  • Advanced queries
  • Reuse of Content
  • Creation of Richer links

To do these, some approaches have been found:

  • Structured blogging
  • Semantic Blogging

12.2.2 Semantic Microblogging

  • SMOB (Semantic Microblogging): Uses FOAF and SIOC, blog posts can embed semantic tags.
  • Smesher
  • StatusNet

Approaches to embed semantics in microblog posts:

  • Microturtle
  • Star Priority Notation
  • Microsyntax

12.2.3 Semantic Wikis:

Benefits: Advanced Queries.


  • Semantic MediaWiki
  • OntoWiki: Does not use markup but uses forms on the interface.
  • SweetWiki: (Semantic Web Enabled Technology Wiki): Does not create ontology instances, but uses seöamt,c wen to augment user experience (such as hierarchical taggings, synonym tags)
  • Dbpedia: Not a wiki, but a semantic database founded via Wikipedia, has a SPARQL endpoint to query. Dataset is free to download.

12.2.4 Semantic Social Bookmarking

  • Twine: NLP and automatic tagging.Site is generated from an ontology in a fundemental way.Has semantic filtering when doing search.
  • Faviki: Uses Dbpedia, Zemanta, Google Language APIs to do multilingual tagging. (so there a many synonym tags.)

12.2.5 Review Websites

Revyu: It is %100 RDF based. It uses many features of Social Web such as star ratings, tags. Has a SPARQL endpoint so it allows mashups with itself

Important Features of Revyu:

  • Revyu can integrate with other Data Sets, using “owl:sameAs”. It can link reviews to other site URIs.
  • Revyu can load FOAF based profiles to itself when users demand.

12.2.6 Social Semantic Web Apps for Sharing Scientific Research


Author stands on real life examples mostly. This makes the article able to be understood more easily. He also detailizes his examples with real code and schemes.

Author’s Conclusions: -

My Conclusions: -

Rating: -

NLP Engineer at PragmaCraft. Former Researcher at Bogazici University Medical Imaging Lab. twitter:ahmetmeleq ///