Time-aware Network Diffusion for Social Network Analytics

Nowadays, social networks, such as Twitter and Facebook, become platforms where ideas and opinions are constantly exchanged and rapidly reach populations that are geographically dispersed. Many marketing, political, and social campaigns rely on this fact to spread ideas, raise awareness in a massive way, and increase the popularity of products and services. Successful campaigns are those that spread information over large fractions of the population as fast as possible, usually within specific deadlines that are required. Generally, there do exist tools that can help design strategies that reach large portions of the population. However, there is a lack of practical tools that can make these strategies meet their required deadlines and achieve their goals as fast as possible. This may heavily impact the success of these campaigns, and this research proposal aims to develop tools that can automate strategies that are efficient both in terms of information spread and the time at which this spread is achieved. By collaborating with a major company in the field, Sysomos Inc., the results of this research can potentially have a large impact in the way that modern social network campaigns are developed.

Faculty Supervisor:

Andreas Veneris

Student:

Zissis Paraskevas Poulos

Partner:

Sysomos Inc.

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Toronto