Introduction to virtual communities overlay networks and social networking. Topics include architectural principles for heterogeneous social networking platforms, trust and reputation as social concepts, agent-based computing, and extraction of trends and patterns from information exchanged between community members. Course requires supervised and unsupervised lab, and intensive programming as a group project and individual assignment.
Intended learning outcomes
Knowledge &understand
To introduce the student to social networking sites as a technology that facilitates the exchange of ideas, information, advantages and disadvantages.
That the student understand the methods of quick access to the content and methods of safe use
To introduce the student with mathematical techniques and graphs of all kinds in the analysis of social networks
To introduce the student with the methods of algorithms used in browsing social networks
To introduce the student with the types of mixed networks and knowledge of new technologies
mental skills
That the student be able to distinguish between types of graphs
That the student arrives at an analysis of the fastest way to reach the desired path.
That the student be able to choose the appropriate algorithm for the solution and distinguish the types of mixed networks.
The student should design a social networking application.
Practical & professional skills
That the student be able to create a user profile with a strong password and the way he connects with friends and communicates between them.
The student performs a correct graph for any type of diagram.
That the student distinguishes the appropriate algorithm to reach the desired path in a faster and safe way.
The student should apply all mathematical techniques in analyzing social networks
The student performs an integrated application to implement all of the above explained in the course.
General and transferable skills
The student should be able to use mathematical techniques and graphs in analyzing any network
The student should be able to use appropriate browsing algorithms.
The student should be able to work in a team to use all types of graphs to represent social networks and the appropriate method of calculation.
That the student be able to deliver an integrated project safely and in the fastest way to reach the required path.
Teaching and learning methods
Theoretical lectures inside the classrooms.
Practical lectures inside the laboratory with the help of teaching assistants in the college.
A panel discussion between the students and in the presence of the professor to obtain new opinions and ideas.
Assignments and tests to activate the students in reaching the best way to solve and discuss it with the professor
Methods of assessments
Midterm exam = 25
discussions = 10
Lab exam = 15
Project = 15
Final exam = 50
Course contents
Introduction to virtual communities overlay networks and social networking
Basic Concepts of Social Network Analysis
Research of SNA: Design, Theorization, and Data Processing
Analysis Strategy
Analysis of Social Networks Based on Traffic Data of Internet Access Service
Analysis of Social Networks Based on the Number of SNS Users
types of social network structures and their structural analysis
social network data analysis
architectural principles for heterogeneous social networking platforms
trust and reputation as social concepts
agent-based computing
Privacy in Online Social Networks
extraction of trends and patterns from information exchanged between community members