Topology and Geometry of the Third-Party Domains Ecosystem: Measurement and Applications
Date Issued
December 19, 2022
Author(s)
DOI
10.1145/3577929.3577932
Abstract
Over the years, web content has evolved from simple text and static images
hosted on a single server to a complex, interactive and multimedia-rich content
hosted on different servers. As a result, a modern website during its loading
time fetches content not only from its owner's domain but also from a range of
third-party domains providing additional functionalities and services. Here, we
infer the network of the third-party domains by observing the domains'
interactions within users' browsers from all over the globe. We find that this
network possesses structural properties commonly found in complex networks,
such as power-law degree distribution, strong clustering, and small-world
property. These properties imply that a hyperbolic geometry underlies the
ecosystem's topology. We use statistical inference methods to find the domains'
coordinates in this geometry, which abstract how popular and similar the
domains are. The hyperbolic map we obtain is meaningful, revealing the
large-scale organization of the ecosystem. Furthermore, we show that it
possesses predictive power, providing us the likelihood that third-party
domains are co-hosted; belong to the same legal entity; or merge under the same
entity in the future in terms of company acquisition. We also find that
complementarity instead of similarity is the dominant force driving future
domains' merging. These results provide a new perspective on understanding the
ecosystem's organization and performing related inferences and predictions.
hosted on a single server to a complex, interactive and multimedia-rich content
hosted on different servers. As a result, a modern website during its loading
time fetches content not only from its owner's domain but also from a range of
third-party domains providing additional functionalities and services. Here, we
infer the network of the third-party domains by observing the domains'
interactions within users' browsers from all over the globe. We find that this
network possesses structural properties commonly found in complex networks,
such as power-law degree distribution, strong clustering, and small-world
property. These properties imply that a hyperbolic geometry underlies the
ecosystem's topology. We use statistical inference methods to find the domains'
coordinates in this geometry, which abstract how popular and similar the
domains are. The hyperbolic map we obtain is meaningful, revealing the
large-scale organization of the ecosystem. Furthermore, we show that it
possesses predictive power, providing us the likelihood that third-party
domains are co-hosted; belong to the same legal entity; or merge under the same
entity in the future in terms of company acquisition. We also find that
complementarity instead of similarity is the dominant force driving future
domains' merging. These results provide a new perspective on understanding the
ecosystem's organization and performing related inferences and predictions.