Network Theory. Social Media Analysis Web Lecture Module – Icarus | Computer Vision

DESCRIPTION

Network theory has very many application areas, where graphs are of primary importance, in e.g.,:

Communication networks
Epidemiology
Systems Biology
Social networks.

Social Media (e.g., Twitter, Facebook, Instagram, to name a few) has had a tremendous growth in the past 20 years. Social Media Analysis has very many applications, e.g.,:

Recommendation Systems
Sentiment Analysis
Information Diffusion
Web Search.

This CVML Web Module focuses on Network Theory and Social Media Analysis, their applications in the above-mentioned diverse domains and the new challenges ahead. Algebraic Graph Analysis lays down the mathematical concepts needed in Network Theory. Graph signal and their processing is described in Graph Signal Processing. Their use in Machine Learning is detailed in Graph Neural Networks.

An Introduction to Social Networks offers the introductory information needed for: a) Recommendation Systems; b) Sentiment Analysis and c) Information Diffusion in social networks. Web Search Based on Ranking is another important application. Blockchain Consensus Algorithms is another very important topic for distributed decision making in nowadays Peer – to – Peer Networks. Cryptocurrencies and other important Blockchain Technology and Applications are detailed as well.

Social media graph.

LECTURE LIST

CVML WEB LECTURE MODULE SCHEDULE

This module has been designed to be mastered within 1 month (or less), if you have proper background (at least early undergraduate student in an EE, ECE, CS, CSE or any Engineering or Exact Sciences Department).
We propose that you follow the above mentioned Lecture order. You may want to skip few Lectures that might not be of immediate interest to you for later study.

On average you can study 4 lectures per week. The related effort is as follows:
Lecture pdf study and filling the related understanding questionnaire: 1-2 hours per lecture (on average, depending on your background).