Data-driven Approaches for Social Video Distribution

TL;DR

This paper explores data-driven methods for social video distribution, addressing challenges in social-aware delivery and proposing a framework that leverages social content propagation to improve user experience.

Contribution

It introduces a comprehensive framework for social video delivery, highlighting the unique characteristics of social sharing and proposing integrated modules for enhanced dissemination.

Findings

Identified key challenges in social-aware video delivery

Proposed a principal data-driven framework for social video distribution

Revealed the importance of social content propagation in user engagement

Abstract

The Internet has recently witnessed the convergence of online social network services and online video services: users import videos from content sharing sites, and propagate them along the social connections by re-sharing them. Such social behaviors have dramatically reshaped how videos are disseminated, and the users are now actively engaged to be part of the social ecosystem, rather than being passively consumers. Despite the increasingly abundant bandwidth and computation resources, the ever increasing data volume of user generated video content and the boundless coverage of socialized sharing have presented unprecedented challenges. In this paper, we first presents the challenges in social-aware video delivery. Then, we present a principal framework for data-driven social video delivery approaches. Moreover, we identify the unique characteristics of social-aware video access and the social content propagation, and closely reveal the design of individual modules and their integration towards enhancing users' experience in the social network context.