CS 491g/691g Special Topics on Social Networks

Department of Computer Science & Engineering

UNR, Spring 2018

Course Information - Prerequisites - Objective - Learning Outcomes - Topics - Textbooks - Similar Courses - Data Resources - Tools - Organization - Research Project - Grading - Schedule

Course Information

Class hours Monday & Wednesday, 1:00 - 2:15pm  Computer Networking: A Top-Down Approach University of Nevada, Reno
Class location PE 105
Instructor Dr. Mehmet H. Gunes
E-mail mgunes (at) unr (dot) edu
Phone (775) 784 - 4313
Web page https://www.cse.unr.edu/~mgunes
Office SEM 216 (Scrugham Engineering-Mines)
Office hours Monday & Wednesday 11:00 - 12:30 am or by appointment

Prerequisites

There is no requirement for strong programming or mathematical skills.

Objective


You may look at earlier course from Fall 2016.


Student Learning Outcomes


Topics (Tentative)

This is a tentative list of topics, subject to modification and reorganization.

Textbooks

Required: Recommended:

Similar Courses


Data Resources


Tools


Organization


Research Project

The main component of your grade is a research project that may materialize as a publication. If your project has a significant coding or computational component (e.g., downloading and analyzing a dataset), then you may work with a partner after consulting with the instructor. The paper will be judged on the following criteria:


Grading (Tentative)

Both grading policy and scale are subject to change.

Grading Policy

Grading Scale

Important Note: You will have one week to appeal for your grades after the graded assignments/tests are returned. So, please keep this in mind if you think that there is a problem/issue with the grading of your work.


Schedule (Tentative), Notes & Assignments

This is a tentative schedule including the exam dates. It is subject to readjustment depending on the time we actually spend in class covering the topics.

Date Lectures Assignments & Notes
Mon, Jan 22 Lecture #1: Introduction to Social Networks The hidden influence of social networks  
Wed, Jan 24 Lecture #2: Introduction to Data Mining Connected: The Power of Six Degrees  
Mon, Jan 29 Lecture #3: Data Preprocessing The Data Science Revolution  
Wed, Jan 31 Lecture #4: Networks  
Mon, Fab 5 Lecture #5: Graph Essentials Project Abstract due  
Wed, Feb 7 Lecture #6: Graph Essentials Lab 1 due  
Mon, Feb 12 Lecture #7: Network Measures  
Wed, Feb 14 Lecture #8: Network Measures Lab 2 due  
Mon, Feb 19 Presidents Day (no class)  
Wed, Feb 21 Lecture #9: Network Models (Random, Small-world)  
Mon, Feb 26 Lecture #10: Network Models (Power-law)  
Wed, Feb 28 Lecture #11: Student presentations Related Work report due  
Mon, Mar 5 Lecture #12: Student presentations  
Wed, Mar 7 Lecture #13: Student presentations Lab 3 due  
Mon, Mar 12 Lecture #14: Student presentations  
Wed, Mar 14 Lecture #15: Student presentations  
Mon, Mar 19 Spring break (no class)  
Wed, Mar 21 Spring break (no class)  
Mon, Mar 26 Lecture #16: Data Mining Essentials  
Wed, Mar 28 Lecture #17: Data Mining Essentials (Supervised Learning) Methodology report due  
Mon, Apr 2 Lecture #18: Data Mining Essentials (Supervised Learning)  
Wed, Apr 4 Lecture #19:Data Mining Essentials (Unsupervised Learning) Lab 4 due  
Mon, Apr 9 Lecture #20: Network Centrality  
Wed, Apr 11 Lecture #21: Community Analysis Lab 5 due  
Mon, Apr 16 Lecture #22: Community Analysis  
Wed, Apr 18 Lecture #23: Information Diffusion  
Mon, Apr 23 Lecture #24: Information Diffusion Lab 6 due  
Wed, Apr 25 Lecture #25: Influence and Homophily  
Mon, Apr 30 Lecture #26: Recommendation  
Wed, May 2 Lecture #27: Behavior Analytics  
Mon, May 7 Lecture #28: Ethical Issues Lab 7 due  
Mon, May 14 Final Project Presentations @ 9:50am Final project report due  

Course Information - Prerequisites - Objective - Learning Outcomes - Topics - Textbooks - Similar Courses - Data Resources - Tools - Organization - Research Project - Grading - Schedule
Last updated on May 7, 2018