Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
1BBM462SOCIAL AND ECONOMIC NETWORKS3+0+03606.09.2024

 
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program COMPUTER ENGINEERING
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course The course aims to teach fundamental principles of Internet based social and economic networks starting from practical problems.
Course Content Methods of page ranking of search engines. Principles of recommender systems. Interactions in social networks. Data pricing methods.
Course Methods and Techniques Lectures
Prerequisites and co-requisities ( BBM104 ) and ( BBM102 )
Course Coordinator None
Name of Lecturers Associate Prof.Dr. Lale Özkahya
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Chiang, M. Networked Life: 20 Questions and Answers, Cambridge University Press, 2012. http://scenic.princeton.edu/network20q/
Course Notes Chiang, M. Networked Life: 20 Questions and Answers, Cambridge University Press, 2012.
http://scenic.princeton.edu/network20q/


Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Midterm Exam 2 % 60
Final examination 1 % 40
Total
3
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 12 6 72
Preparation for Midterm Exam 2 20 40
General Exam Preparation 1 20 20
Total Work Load   Number of ECTS Credits 5,8 174

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 A student who took this course can: Explain how search engines rank web pages.
2 Explain how shopping and movie web sites recommend products to their users.
3 Explain the principles of interactions between humans in social networks.
4 Explain the concept of social distance.
5 Explain the fundamental principles of data and ad pricing
6  
7  
8  

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to the course
2 Auctions for ad spaces on the Internet
3 Page ranking methods of search engines
4 Recommender systems for movie and shopping sites.
5 Methods for product ranking and sorting for shopping sites.
6 Midterm
7 Principles of crowdsourced web sites (e.g. Wikipedia)
8 Content distribution across social networks
9 Small World phenomenon in social networks
10 Midterm
11 Bottleneck analysis of the Internet architecture
12 Pricing data transfers
13 Smart pricing methods
14 Preparation for the final exam
15 Preparation for the final exam
16 Final exam

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
All 5 5 5 2 2 1 1 1 1 1 1
C1
C2
C3
C4
C5
C6
C7
C8

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

  
  https://bilsis.hacettepe.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=2687569&lang=en