The Strength of Structural Diversity in Online Social Networks.

ABSTRACT: Understanding the way individuals are interconnected in social networks is of prime significance to predict their collective outcomes. Leveraging a large-scale dataset from a knowledge-sharing website, this paper presents an exploratory investigation of the way to depict structural diversity in directed networks and how it can be utilized to predict one's online social reputation. To capture the structural diversity of an individual, we first consider the number of weakly and strongly connected components in one's contact neighborhood and further take the coexposure network of social neighbors into consideration. We show empirical evidence that the structural diversity of an individual is able to provide valuable insights to predict personal online social reputation, and the inclusion of a

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC8328400 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature