Network Models: Random Networks, Scale-Free Networks, Barabási-Albert Model, Fuzzy-Granular Social Network, Generating Network Data
Game Theory and Network Traffic Modeling
Information Cascade, Epidemic spread modeling,
Small-World
Community Detection Problem
Link Prediction Problem
Evolving Network and Temporal Network
Python NetworkX
Learning Materials
Textbook
Networks, Crowds, and Markets: Reasoning About a Highly Connected World, by David Easley and Jon Kleinberg, (Cambridge University Press - Sep 2010) - Prepublication draft available online. http://www.cs.cornell.edu/home/kleinber/networks-book/
Network Science, by Albert-Laszlo Barabasi, (Cambridge University Press - August 2016) freely available under the Creative Commons licence. http://www.networksciencebook.com/
Networks, by Mark Newman, (Oxford University Press, 2nd-edition - Sep 2018)
Reference Books
Complex and Adaptive Dynamical Systems, by Claudius Gros, (Springer, 4th Edition - 2015).
The Structure of Complex Networks Theory and Applications, by Ernesto Estrada, (Oxford University Press - Dec 2011).
Exploratory Social Network Analysis with Pajek, by Wouter de Nooy, Andrej Mrvar, and Vladimir Batagelj, (Cambridge University Press, 3rd Edition - July 2018)
As per the notification from academics 100% attendance is mandatory. If you have genuine reason please take leave approval as per academics rule.
If attendance falls below 75%, one should get at least C grade to pass the course. Otherwise F grade will be assigned.
Grading Policy
Interactive Videos
Quizzes (Moodle)
Project
10%
10%
30%
Coding Assignment
Minors
Major
10%
10% + 10%
20%
Interactive Video (Moodle)
All the topics in the syllabus is covered in interactive videos where all the videos are embedded with questions. Answer the questions and get the grades. You can try as many times as you wish and improve your scores.
Quizzes (Moodle)
There will be about 4-6 quizzes; best 3/4 will be considered for grading.
All the quizzes will be in Moodle Platform.
No makeup quiz will be taken considering there will be more than required no of quizzes.
Coding Assignments
There will be many coding assignments, about 8-10.
Least 2 scores will not be consider for grading.
Preferably with NetworkX in Python
Project
Report: 30%, Presentation: 20%, Project Work: 50%
Grading will be based on:
Organization: Applicable to Reports and Presentations
Clarity: Applicable to Reports/Presentation/Work/Interaction
Length: Too Short/Too Long will be penalized (report/presentation)
References: Correct and Comprehensive References
Correctness: Applicable to Development and Contributory Work
Significance/Coverage: Significance for Contributory Work, Coverage for Survey/Review
Originality: Plagiarized Content of any form (textual, formulation, images, results) will mark zero for the project component.
Contribution: Quality of Contribution
Consideration for A* Grade: Paper submission to above average conference (at least) along with total no of marks.
Project can be done in groups not more than two members.
Important Dates:
10/Aug: Last date of group identification
17/Aug: Topics will be floated
31/Aug: Last date for Topic selection
06/Oct: Mid-term project assessment presentation
08/Oct: ^^ if necessary
31/Oct: Abstract Submission
6/Nov: Report Submission
10/Nov: Feedback Release
17/Nov: Revision Submission
Presentation dates will be announced (tentative: Nov 5, 10, 12)
Quiz dates will be announced during class
Plagiarism tolerance is 7% from single source and 15% cumulative, anything more will reduce your marks as follows:
Any logical/conceptual/formulation plagiarism: zero marks
Other form of plagiarism (above 50%): zero marks
Otherwise: Percentage of plagiarism will be deducted from the obtained mark