Efficient Analytics over Hidden Online Social Networks
Abstract
The main objective of the project is to develop efficient analytics techniques for understanding the state of an online social network, from the organic data generated by the social network users to the behavior of these users, from the growth or decline of the social network to the user-user or user-data interactions that may contribute to such changes. The term online social network has a broad definition in our project, encompassing both the traditional meaning, i.e., a graph structure where nodes are users and edges represent the relationships explicitly declared by users between each other, to virtual networks where the nodes could be organizations or groups of users and the edges could be tacitly defined by common activities, proximity of locations, similarities of opinions, or other relationships not explicitly declared by users but implicitly inferable from data available on the online social network.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 06, 2019
- Accession Number
- AD1091109
Entities
People
- Gautam Das
Organizations
- University of Texas at Arlington