Social Networks



Prof. Sudarshan Iyengar

Prof. Yayati Gupta

IIT Ropar

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SKU: IIT Ropar Category:



The world has become highly interconnected and hence more complex than ever before. We are surrounded by a multitude of networks in our daily life, for example, friendship networks, online social networks, world wide web, road networks etc. All these networks are today available online in the form of graphs which hold a whole lot of hidden information. They encompass surprising secrets which have been time and again revealed with the help of tools like graph theory, sociology, game theory etc. The study of these graphs and revelation of their properties with these tools have been termed as Social Network Analysis.


Any Interested Learners


Prof. Sudarshan Iyengar, Associate Professor at the CSE at IIT Ropar has a Ph.D. from the Indian Institute of Science (IISc). An exemplary teacher who has delivered over 350 popular science talks to students of high school and advanced graduate programmes. Dr. Sudarshan has offered more than 100 hours of online lectures with novel teaching methodologies that have reached lakhs of Students. His research interests include Data Sciences, Social Computing, Social Networks, Collective Intelligence, Crowdsourced Technologies and Secure Computation

Prof. Yayati Gupta is an Assistant Professor in the Computer Science & Engineering Department at Mahindra University École Centrale School of Engineering. She is also an instructor for a couple of NPTEL/SWAYAM courses (Social Networks, Joy of Computing). She holds a Ph.D. in Computer Science and Engineering from Indian Institute of Technology Ropar (November 2017). Her research primarily focuses on Social Network Analysis and Complex Networks. The major research projects include “Modeling Information Diffusion” and “Understanding Virality of Internet Memes” in online social networks.

Certification Process

1. Join the course
Learners may pay the applicable fees and enrol to a course on offer in the portal and get access to all of its contents including assignments. Validity of enrolment, which includes access to the videos and other learning material and attempting the assignments, will be mentioned on the course. Learner has to complete the assignments and get the minimum required marks to be eligible for the certification exam within this period.

COURSE ENROLMENT FEE: The Fee for Enrolment is Rs. 3000 + GST

2. Watch Videos+Submit Assignments
After enrolling, learners can watch lectures and learn and follow it up with attempting/answering the assignments given.

3. Get qualified to register for exams
A learner can earn a certificate in the self paced course only by appearing for the online remote proctored exam and to register for this, the learner should get minimum required marks in the assignments as given below:

Assignment score = Score more than 50% in at least 9/12 assignments.
Exam score = 50% of the proctored certification exam score out of 100
Only the e-certificate will be made available. Hard copies will not be dispatched.”

4. Register for exams
The certification exam is conducted online with remote proctoring. Once a learner has become eligible to register for the certification exam, they can choose a slot convenient to them from what is available and pay the exam fee. Schedule of available slot dates/timings for these remote-proctored online examinations will be published and made available to the learners.

EXAM FEE: The remote proctoring exam is optional for a fee of Rs.1500 + GST. An additional fee of Rs.1500 will apply for a non-standard time slot.

5. Results and Certification
After the exam, based on the certification criteria of the course, results will be declared and learners will be notified of the same. A link to download the e-certificate will be shared with learners who pass the certification exam.


Course Details

Week 1: Introduction
Week 2: Handling Real-world Network Datasets
Week 3: Strength of Weak Ties
Week 4: Strong and Weak Relationships (Continued) & Homophily 
Week 5: Homophily Continued and +Ve / -Ve Relationships 
Week 6: Link Analysis 
Week 7: Cascading Behaviour in Networks
Week 8: Link Analysis (Continued) 
Week 9: Power Laws and Rich-Get-Richer Phenomena 
Week 10: Power law (contd..) and Epidemics 
Week 11: Small World Phenomenon
Week 12: Pseudocore (How to go viral on web)

Books and References:

  1. Networks, Crowds and Markets by David Easley and Jon Kleinberg, Cambridge University Press, 2010
    (available for free download).
  2. Social and Economic Networks by Matthew O. Jackson, Princeton University Press, 2010.


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