The purpose of this course is to provide a theoretical and practical survey of graph theory and its application on social networks. Graph theory is a popular subject used in many modern applications and graphs are used to solve many problems in different types of fields. Firstly, this course provides an introduction to the basic concepts of graphs and graph theory, and aims to cover a range of topics starting from special graphs to different usage areas of graphs such as random, communication and especially social networks., Our goal is to establish a functional understanding of social networks, which are both very popular type of network application and also challenging topic in research area.
Prerequisite(s)
Course Code Course Name…
Corequisite(s)
Course Code Course Name…
Special Requisite(s)
The minimum qualifications that are expected from the students who want to attend the course.(Examples: Foreign language level, attendance, known theoretical pre-qualifications, etc.)
Classrooms are adequately equipped for this course. This course does not require separate lab equipments. Computer hardware in classrooms and/or open computing labs are suffıcient for this course. The department has the faculty expertise and available staff to offer this course. The course is designed to leverage open source softwares and learning resources. No proprietary softwares are needed.
Due to the dynamic nature of this subject there would be no textbooks, however, some classic social network analysis literature would be used to build the foundations and cover the fundamentals. Most of the reference materials would be borrowed from several books and online resources and will be disseminated to the students in the form of lecture slides, notes, handouts, in-class exercises, assignments, and projects.
Principle Sources
Some of the existing and classical literature on social network analysis which would be briefly followed are:
- Any book and lecture notes on graphs and graph theory
- Graph Theory and Complex Networks - An Introduction, Maarten van Steen
- Lecture notes on Graph Theory and Social Networks, Kimball Martin
- Lab materials and notes
Other Sources
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Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction of the course, course syllabus, grading, office hours, Introduction to graph theory concept
Introduction of the lab details, course syllabus, grading, lab methods
2. Week
Types of graphs, graph terminology, graph models
Lab exercices, problem solving about graph models
3. Week
Basic theorems for vertices and edges, special types of simple graphs, bipartite graphs, subgraphs
Lab exercices, problem solving about special graph types, degree calculations, subgraphs
4. Week
Representing graphs, adjacency and incidence, isomorphism
Lab exercices, problem solving about graph representation and isomorphism
5. Week
Connectivity, paths and circuits
Lab exercices, problem solving about paths and circuits
6. Week
Euler and Hamilton paths/circuits
Lab exercices, problem solving about Euler paths, Hamilton paths, real world examples for usage of them
7. Week
Shortest path problems, their usage in different types of special networks
Lab exercices, problem solving about shortest path problems, Dijkstra algorithm
8. Week
Midterm
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9. Week
Planar Graphs and Graph Coloring, Random Networks
Lab exercices, problem solving about planar graphs and real world graph coloring examples
10. Week
Random Networks, Erdös-Renyi networks
Lab examples and scenarios about random networks
11. Week
Modern computer networks, peer-to-peer overlay networks
Lab examples and scenarios about communication networks
12. Week
Social Networks, Social Network Models
Lab examples and scenarios about social networks
13. Week
Social networks analysis and metrics
Lab exercices, problem solving about social network analysis
14. Week
Social networks analysis and metrics
Lab exercices, problem solving about social network analysis
15. Week
16. Week
17. Week
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
40
Homework / Term Projects / Presentations
1
20
Final Exam
1
40
Program Outcomes
PO-1
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
PO-2
Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
PO-3
Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
PO-4
Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
PO-5
Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.
PO-6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
PO-7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language.
PO-8
Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
PO-9
Awareness of professional and ethical responsibility.
PO-10
Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
PO-11
Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.
Learning Outcomes
LO-1
-Explain how the means of communication are shaped by complex social factors;
LO-2
-Students will have been introduce to the state-of-the art developments in social computing, to study emerging challenges & research opportunities with social media, and to learn innovatively applying multidisciplmary approaches to problem solving.
LO-3
-Understand the impact of communication in social networking.
LO-4
-Analyze the changing nature of media and communication institutions from a number of theoretical perspectives;
LO-5
-Students will enhance their problem solving skills, challenge their thinking boundaries, take advantage of opportunities for being creative, as well as learn and produce exciting stuff.
LO-6
-Engage critically with media discourses of communication and information technology.
LO-7
-Given this unique set of expertise, students will be prepared for the increasing demands in IT industry and for taking on in-depth advanced research in the web sciences.
