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Impact of Using Semantic Social Networks On Organizations. Zahra Amin Nayeri Ali Fatalian University of Tehran. Presentation Outline. Centeralization or Decentralization ? SEBSON Framework: a Se mantic b ased So cial N etwork Framework Implementation and test Issues
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Impact of Using Semantic Social Networks On Organizations Zahra Amin Nayeri Ali Fatalian University of Tehran
PresentationOutline • Centeralization or Decentralization ? • SEBSON Framework: a Semantic based Social Network Framework • Implementation and test Issues • Semantic Social Networks VS. Non Semantic Social Networks
Introduction Increasing tendency toward decentralized structure in business world.
Introduction • Chaos and disorder ? • Constituents of a decentralized organization : • Workgroups • Catalysts • Controllers
Introduction Benefits of using semantic social networks : 1- It reduces the risks associated with decentralization. 2-It reacts faster to changes in environment and organization.
Introduction 3- It generates SN’s and social mining resources faster and cheaper. 4- Improves workflow , synergy and cooperation. 5- Enables easier monitoring and management.
Introduction • SEBSON framework. • Objectives : • To prove the superiority of decentralization in certain environments. • To study abilities enabled by using SEBSON. • Two real world test cases .
Centralization or Decentralization ? • Decentralized Organization : • Norms Rather than rules. • Distribution of Power. • Faster decision making and reaction to change • Efficiency and Performance. • Entrepreneurship
Centralization or Decentralization ? • Hybrid Structure • Has pros of both structures: • Bottom up decision making • Adaption to change
Centralization or Decentralization ? Partitions Work groups Cores
Semantic Web Technologies • Resource Description Framework (RDF) • RDF schema (RDFS) • Dublin Core ™ • Friend of a Friend ( FOAF ) • Jena Semantic Web Framework
Semantic Web Technologies • Dublin Core RDF and Ontologies : • used to describe business procedures. • FOAF : • Social Interactions between workgroups and partitions
Semantic Web Technologies • Reasoning & Knowledge management: • Jena Inference Engine • SPARQL language • RDF triplet stores And SDB layer • Agents : • Social Network Inspector • Social Network Analyzer • Project Manager
SEBSON Framework Programmers & Administrators Users Agents
Environment Issues • Not all environments are suitable for decentralization. • Environment requirements : • Change with fast pace. • Shared interests and functionalities. • Need for synergy and cooperation
Simulation Issues • Process : • Finding possible relations using RDF & DC descriptions • Establishing new relations and updating FOAF tags • Results : • Semantic social network. • Information about structure of organization
Semantic Social Networks VS. Non Semantic Social Networks • Non Semantic Social Network Visualization :
Semantic Social Networks VS. Non Semantic Social Networks • Semantic Social Network Visualization :
Semantic Social Networks VS. Non Semantic Social Networks • SSN : • Better Synergy and Cooperation • Better decision making and adaption to change • Reducing dependency • Better distribution of power • Better adaption to change
Bi - components • SSN : • More reliable • More dependable
Number of K-Cores • SSN : • Relations take place upon projects as opposed to hierarchical positions in SN • Better Synergy and Cooperation
AverageAggregateConstraint • SSN : • More Flexibility • More Adaptability to change • Better Entrepreneurship in workgroups
Betweeness • SSN : • Workgroups are actively in flow of information • Faster and Better Decision Making • Independency of workgroups • More efficiency and performance
Conclusions • Semantic web technologies can be used to ease decentralization • Decentralization benefits were proved : • Synergy • Decision making • Flexibility • Reliability • Adaptability to change • Performance • Efficiency
Conclusions • Additional advantages of using Semantic social networks in organizations : • Providing tools for better management and control • Presenting structural information for social network mining • Making partner finding and recruiting easier