Social Network Analysis

By Prof. Tanmoy Chakraborty | IIT Delhi

Learners enrolled: 297

ABOUT THE COURSE:

Networks are a fundamental tool for modeling complex social, technological, and biological systems. Coupled with the emergence of online social networks and large-scale data availability in social sciences, this course focuses on the analysis of massive networks which provide many computational, algorithmic, and modeling challenges. The course will cover research on the structure and analysis of such large networks and on models and algorithms that abstract their basic properties. We will explore how to practically analyze large-scale network data and how to reason about it through models for network structure and evolution. Topics covered in this course are how information spreads through society; robustness and fragility of networks; algorithms for the World Wide Web; prediction and recommendation in online social networks; representation learning for large networks; etc.

PREREQUISITES: Python programming, Probability and Statistics, Machine Learning

INDUSTRY SUPPORT: Any social media company, E-commerce company, etc

Summary

Course Status :	Upcoming
Course Type :	Elective
Duration :	12 weeks
Category :	Computer Science and Engineering
Credit Points :	3
Level :	Undergraduate/Postgraduate
Start Date :	24 Jul 2023
End Date :	13 Oct 2023
Enrollment Ends :	31 Jul 2023
Exam Registration Ends :	18 Aug 2023
Exam Date :	28 Oct 2023 IST

Note: This exam date is subjected to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1: Introduction ; Tutorial 1: Introduction to Python/Colab ; Tutorial 2: Introduction to NetworkX - Part I

Week 2: Network Measures ; Tutorial 3: Introduction to NetworkX - Part II
Week 3: Network Growth Models

Week 4: Link Analysis
Week 5: Tutorial 4: Graph Visualization Tools ; Community Detection - Part I

Week 6: Community Detection - Part II

Week 7: Link Prediction

Week 8: Cascade Behavior and Network Effects

Week 9: Anomaly Detection

Week 10: Introduction to Deep Learning ; Graph Representation Learning - Part I

Week 11: Graph Representation Learning - Part II ; Tutorial: Coding on Graph Representation Learning

Week 12: Applications and Case Studies ; Conclusion

Books and references

Social Network Analysis, Tanmoy Chakraborty, Wiley, 2021
Network Science, Albert-Lazzlo Barabasi
Social Network Analysis: Methods and Applications, Stanley Wasserman, Katherine Faus

Instructor bio

Prof. Tanmoy Chakraborty

IIT Delhi

I am an Associate Professor in the Dept. of Electrical Engineering, Indian Institute of Technology Delhi (IIT Delhi), India since September 2022. I am also an associate faculty of the Yardi School of Artificial Intelligence, IIT Delhi. I am an ACM’s Distinguished Speaker (2023-2025). I was a Ramanujan Fellow from 2018-2023. Before joining IIT Delhi, I served as an Assistant Professor (May 2017 - Dec 2021) and an Associate Professor (Jan 2022 - Aug 2022) in the Dept of CSE, Indraprastha Institute of Information Technology Delhi (IIIT Delhi), India. I also served as the head of the Infosys Centre for AI (CAI) at IIIT Delhi before joining IIT Delhi. I obtained my PhD as a Google PhD scholar from the Dept. of CSE, Indian Institute of Technology, Kharagpur, India in September, 2015. Following this, I joined University of Maryland, College Park as a Postdoctoral Researcher. My broad research interests include Natural Language Processing, Graph Neural Networks, and Social Computing.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: 28 October 2023 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Madras .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team

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