Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media
Abstract
Influence cascades are typically analyzed using a single metric approach, i.e., all influence is measured using one number. However, social influence is not monolithic; different users exercise different influences in different ways, and influence is correlated with the user and content-specific attributes. One such attribute could be whether the action is an initiation of a new post, a contribution to a post, or a sharing of an existing post. In this paper, we present a novel method for tracking these influence relationships over time, which we call influence cascades, and present a visualization technique to better understand these cascades. We investigate these influence patterns within and across online social media platforms using empirical data and comparing to a scale-free network as a null model. Our results show that characteristics of influence cascades and patterns of influence are, in fact, affected by the platform and the community of the users.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 28, 2021
- Source ID
- 10.3390/e23020160
Entities
People
- Chathika Gunaratne
- Chathura Jayalath
- Chathurani Senevirathna
- Ivan I Garibay
- William Rand
Organizations
- Defense Advanced Research Projects Agency