Revisiting Information Diffusion Beyond Explicit Social Ties: A Study of Implicit-Link Diffusion on Twitter
Yuto Tamura, Sho Tsugawa, Kohei Watabe

TL;DR
This paper investigates how implicit links, beyond explicit social ties, influence information diffusion on Twitter, revealing their role in spreading content across distant communities and their association with user attributes.
Contribution
It provides a large-scale analysis of implicit links on Twitter, showing their impact on diffusion patterns and the distribution of user attributes involved in implicit link formation.
Findings
Implicit links are more likely used by users farther from the source.
Implicit links contribute less volume but connect distant communities.
User attributes linked to implicit links show moderate homophily and monophily.
Abstract
Information diffusion on social media platforms is often assumed to occur primarily through explicit social connections, such as follower or friend ties. However, information frequently propagates beyond these observable ties -- through external websites, search engines, or algorithmic recommendations -- creating implicit links. How the presence of implicit links affects the diffusion process remains unclear. In this study, we investigate the characteristics of implicit links on Twitter using four large-scale datasets. Our analysis reveals that users who are farther from the original source in the social network are more likely to engage in diffusion via implicit links. Although implicit links contribute less to the overall diffusion volume than explicit links, they play a distinct role in disseminating content across diverse and topologically distant communities. We further examine the…
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