The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Social Networks and Semantics
|
|
Author(s): Ioan Toma (University of Innsbruck, Austria), James Caverlee (Texas A&M University, USA), Ying Ding (Indiana University, USA), Elin K. Jacob (Indiana University, USA), Erjia Yan (Indiana University, USA)and Staša Milojevic (Indiana University, USA)
Copyright: 2011
Pages: 42
Source title:
Social Computing Theory and Practice: Interdisciplinary Approaches
Source Author(s)/Editor(s): Panagiota Papadopoulou (University of Athens, Greece), Panagiotis Kanellis (University of Athens, Greece)and Drakoulis Martakos (University of Athens, Greece)
DOI: 10.4018/978-1-61692-904-6.ch009
Purchase
|
Abstract
This chapter discusses the relation between Social Networks and Semantics – two areas that have recently gained a lot of attention from both academia and industry. The authors show how synergies between these two areas can be used to solve concrete problems, and they describe three approaches that demonstrate the potential for interconnecting these technologies. The first approach focuses on the semantic profiling of social networks. More precisely, they study the characteristics of large online social networks through an extensive analysis of over 1.9 million MySpace profiles in an effort to understand who is using these networks and how they are being used. The MySpace study is based on a comparative analysis of three distinct but related facets: the sociability of users in MySpace; the demographic characteristics of MySpace users; and the text artifacts of MySpace users. The second approach to interconnecting social networks and semantics focuses on a solution for mediating between social tagging systems. The Upper Tag Ontology (UTO) is proposed to integrate social tagging data by mediating between related social metadata schemes. The chapter discusses how UTO data can be linked with other social metadata (e.g., FOAF, DC, SIOC, SKOS), how to crawl and cluster tag data from major social tagging systems, and how to integrate data using UTO. The third approach discusses the use of social semantics to qualitatively improve the task of service ranking. The authors explore the idea of using social annotation technologies for ranking web services and show how such an approach can be implemented using information provided by Delicious, one of the largest social networks.
Related Content
|
Nitesh Behare, Rashmi D. Mahajan, Meenakshi Singh, Vishwanathan Iyer, Ushmita Gupta, Pritesh P. Somani.
© 2024.
36 pages.
|
|
Shikha Mittal.
© 2024.
21 pages.
|
|
Albérico Travassos Rosário.
© 2024.
31 pages.
|
|
Carla Sofia Ribeiro Murteira, Ana Cristina Antunes.
© 2024.
23 pages.
|
|
Mario Sierra Martin, Alvaro Díaz Casquero, Marina Sánchez Pérez, Bárbara Rando Rodríguez.
© 2024.
17 pages.
|
|
Poornima Nair, Sunita Kumar.
© 2024.
18 pages.
|
|
Neli Maria Mengalli, Antonio Aparecido Carvalho.
© 2024.
16 pages.
|
|
|