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.
LECTURE LIST
- Algebraic Graph Analysis
- Blockchain Consensus Algorithms
- Graph Signal Processing
- Graph Neural Networks
- Information Diffusion
- Introduction to Social Networks
- Recommendation Systems
- Sentiment Analysis
- Web Search Based on Ranking