Information spread in online social media (ISOSM)
Main funder
Funder's project number: FA9550-17-1-0030
Funds granted by main funder (€)
- 149 113,00
Funding program
Project timetable
Project start date: 15/03/2017
Project end date: 14/03/2020
Summary
The goal of the present research is to study viral information spread occurring
in social media sites. This phenomenon is referred to as information cascades. The pro-
posed study will investigate properties of massive real world information cascades, collected
from social media site VK.com. Specifically, a set of metrics for quantitative description of
cascades (such as size, speed, and depth) is going to be introduced; then effect of individ-
ual nodes and cohesive groups on these metrics is going to be analyzed. Part of the aim
of this research is to formulate critical nodes detection problem with regard to minimiza-
tion of various metrics of information cascades, and develop the method for its efficient
computation.
Overall, the present research will combine methodologies used in operations research
with computer science methods, and validate the results using large sets of real world social
media data.
in social media sites. This phenomenon is referred to as information cascades. The pro-
posed study will investigate properties of massive real world information cascades, collected
from social media site VK.com. Specifically, a set of metrics for quantitative description of
cascades (such as size, speed, and depth) is going to be introduced; then effect of individ-
ual nodes and cohesive groups on these metrics is going to be analyzed. Part of the aim
of this research is to formulate critical nodes detection problem with regard to minimiza-
tion of various metrics of information cascades, and develop the method for its efficient
computation.
Overall, the present research will combine methodologies used in operations research
with computer science methods, and validate the results using large sets of real world social
media data.
Principal Investigator
Primary responsible unit
Follow-up groups
Related publications and other outputs
- Multitask deep learning for native language identification (2020) Habic, Vuk; et al.; A1; OA
- Network-based indices of individual and collective advising impacts in mathematics (2020) Semenov, Alexander; et al.; A1; OA
- Exploring social media network landscape of post-Soviet space (2019) Semenov, Alexander; et al.; A1; OA
- Graph-based exploration and clustering analysis of semantic spaces (2019) Veremyev, Alexander; et al.; A1; OA
