The main goal was to develope a Social Network Analysis system, that served to
guide any user with no experience in the SNA to detect communities, find the influencer and perform other tasks on a social
network.
Project's Details
About the project
Social Network Analysis aims to detect communities inside a network. Since researchers proposed many approaches,
the decision of choosing one method as a task requires experience in the field of social networks.
In this project, a defacto standard validation measure (Modularity) was applied to guide any user with no
experience in Social Network Analysis in choosing one algorithm for detecting communities.
In addition to that, some functionalities were added to the system such as finding the influencer,
calculating some centrality measures, and the ability to compare community detection algorithms.
Final Product
The final product of the project is a program where a user can perform the following tasks:
- Upload a file of a social network dataset to be analyzed.
- Figure out the recommended algorithms to be applied on the dataset to detect communities in that network.
- Detect different communities using recommended algorithm.
- Detect the influencer in the social network
- Plot the social network
- Compare the results of different algorithms for detecting the communities
To check a scenario of using the product, please check the project in GitHub.
Skills covered in this project
- Skills
Network Analysis, Social Network Analysis.
- Programing language
R.
- Tools, Libraries, and Softwares
R studio enviroment.