Click to Print This Page
Code ENS 48002
Term 201701
Title Special Topics in FENS: Analysis of Social Networks
Faculty Faculty of Engineering and Natural Sciences
Subject Engineering Sciences(ENS)
SU Credit 3
ECTS Credit 6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Instructor(s) Ali Rana At?lgan,
Language of Instruction English
Level of Course Undergraduate
Type of Course Click here to view.
(only for SU students)
Mode of Delivery Formal lecture,Interactive lecture
Planned Learning Activities Interactive,Discussion based learning


Which network structures favor the rapid spread of new ideas, behavior, or technologies? Under what circumstances can a minority of individuals influence an exceptional number of their peers? Our technological and financial-economical systems have become dependent on networks of considerable complexity. This has made the behavior of these systems difficult to reason and hence made them susceptible to disruptions that transform localized events into cascading failures. The emergence of pervasive data on human mobility, migration and communication has ferreted out patterns that may answer such questions and that constitute thorough understanding via simple models.
In this course, we will set the stage with examples/phenomena. Then with qualitative thought experiments and quantitative simple models, we will crystallize our thinking. Coding language is Python. We shall try to understand if a principle or a recurring observation may hold across many settings with broader implications. Curiosity, persistence, and perseverance are essential both to contribute to the moderation of the course and to benefit from the learning outcomes.

Learning Outcome

Calculate measures pertinent to thorough analysis of networks, including mean coordination cumber, clustering coefficient, embeddedness, neighborhood overlap, average path length, betweenness centrality, and their distributions
Determine bridges and local bridges in the networks and calculate betweenness centrality of nodes and links, and perform graph partitioning
Detect if the given network is balanced or unbalanced and analyze if the growth of the network changes its character
Estimate if more than a couple of common friends or common focus groups increase the propensity of constructing a new link between any arbitrary elements of the network
Check if homophily exist in the network under consideration and analyze the roots if it is due to mutable (inverse selection) or immutable (selection) characteristics
Calculate the properties of random, small-world, and power law networks and analyze a network data in order to classify its type
Determine which network structures facilitates more the spread of virus, fashion, ideas, behavior, or technologies and what are the common factors of efficient diffusion in networks

Programme Outcomes
Common Outcomes For All Programs
1 Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 4
2 Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 4
3 Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects. 3
4 Communicate effectively in Turkish and English by oral, written, graphical and technological means. 2
5 Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 2
Common Outcomes ForFaculty of Eng. & Natural Sci.
1 Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 4
2 Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose. 4
3 Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 4
4 Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 3
5 Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 3
6 Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 2
7 Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility. 3
Electronics Engineering Program Outcomes Area Electives
1 Use mathematics (including derivative and integral calculations, probability and statistics), basic sciences, computer and programming, and electronics engineering knowledge to design and analyze complex electronic circuits, instruments, software and electronics systems with hardware/software. 1
2 Analyze and design communication networks and systems, signal processing algorithms or software using advanced knowledge on differential equations, linear algebra, complex variables and discrete mathematics. 2
Materials Science and Nano Engineering Program Outcomes Area Electives
1 Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 1
2 Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 1
3 Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 1
Mechatronics Engineering Program Outcomes Area Electives
1 Familiarity with concepts in statistics and optimization, knowledge in basic differential and integral calculus, linear algebra, differential equations, complex variables, multi-variable calculus, as well as physics and computer science, and ability to use this knowledge in modeling, design and analysis of complex dynamical systems containing hardware and software components. 2
2 Ability to work in design, implementation and integration of engineering applications, such as electronic, mechanical, electromechanical, control and computer systems that contain software and hardware components, including sensors, actuators and controllers. 1
Industrial Engineering Program Outcomes Area Electives
1 Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics. 3
2 Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 3
3 Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 3
Assessment Methods and Criteria
  Percentage (%)
Midterm 80
Exam 20
Recommended or Required Reading

Easley, D. and J. Kleinberg, Networks, Crowds, and Markets - Reasoning about a Highly Connected World. Cambridge University Press, 2010.