Social Network Analysis (DA 516)

2021 Spring
Faculty of Engineering and Natural Sciences
Data Analytics(DA)
3
6
Ahmet Onur Durahim onurdurahim@sabanciuniv.edu,
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Doctoral, Master
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CONTENT

Different types of social networks and connectivity are a crucial part of the underlying models of the new generation of applications we use. These connections include people, places, activities, businesses, products, social and integrated business processes happening in personal and business networks or communities. In this course we will study different applications such as Facebook, Twitter, Linkedin and Foursquare, and discover different networks formed by the connectivity. We will introduce tools that will give us insight into how these networks function: We will introduce fundamentals of graph theory and discover how these graphs can be modeled and analyzed (Social Network Analysis). We will also study the interaction dynamics using game theory. Learning objectives are: 1. Study different social applications and how they can be modeled. 2. Understand the basics of graph theory. 3. Understand and perform basic social network analysis 4. Understand the basics of game theory 5. Apply these concepts to model the Web and new social applications.

PROGRAMME OUTCOMES


1. Develop the ability to use critical, analytical, and reflective thinking and reasoning

2. Reflect on social and ethical responsibilities in his/her professional life.

3. Gain experience and confidence in the dissemination of project/research outputs

4. Work responsibly and creatively as an individual or as a member or leader of a team and in multidisciplinary environments.

5. Communicate effectively by oral, written, graphical and technological means and have competency in English.

6. Independently reach and acquire information, and develop appreciation of the need for continuously learning and updating.


1. Design and model engineering systems and processes and solve engineering problems with an innovative approach.

2. Establish experimental setups, conduct experiments and/or simulations.

3. Analytically acquire and interpret data.


1. To have acquired basic theoretical knowledge and technical infrastructure in the field of cyber security

2. To have developed a deep experience and understanding on the basic methods and human-induced and techinal weaknesses followed by the existing and future cyber attacks, threats and counterfeiting

3. To be able to analyze an IT infrastructure comprehensively and to determine risk by monitoring the existing weaknesses and to determine a cyber security strategy

4. To take the necessary measures to prevent possible costs and destruction during the occurrence of cyber attacks,

5. To be able to use current cyber security software tools and related software for professional purposes,

6. To follow the cyber security intelligence news and to combine and analyze data from different sources to take measures for preventing or reducing the prospective cyber attacks,

7. To be able to take preventive measures to hinder possible drawbacks by creating a deep understanding and awareness in legal, ethical and social aspects of protecting the security and privacy of personal and corporate data.


1. Comprehend the conceptual foundations of analytical methods and techniques within the scope of business analytics,

2. Acquire theoretical and practical knowledge on applied information systems by developing fundamental programming skills,

3. Improve decision making by turning high-volume data into useful information and integrating data analysis tools

4. Turn high-volume data into useful information by using quantitative models and understanding and managing data analysis techniques, communicate and visualize the results for business use

5. Understand the data quality, data integrity and data accuracy concepts, and occupational ethics regarding data privacy and intellectual property