Internet interconnections are the means by which networks exchange traffic between one another. These interconnections are typically established in facilities that have known geographic locations, and are owned and operated by so-called colocation and interconnection services providers (e.g., Equinix, CoreSite, and EdgeConneX). These previously under-studied colocation facilities and the critical role they play in solving the notoriously difficult problem of obtaining a comprehensive view of the structure and evolution of the interconnections in today's Internet are the focus of this paper. We present mi2, a new approach for mapping Internet interconnections inside a given colocation facility.1We infer the existence of interconnections from localized traceroutes and use the Belief Propagation algorithm on a specially defined Markov Random Field graphical model to geolocate them to a target colocation facility. We evaluate mi2by applying it initially to a small set of US-based colocation facilities. In the process, we compare our results against those obtained by two recently developed related techniques and discuss observed discrepancies that derive from how the different techniques determine the ownership of border routers. As part of our validation approach, we also identify drastic changes in today's Internet interconnection ecosystem (e.g., new infrastructures in the form of “cloud exchanges” that offer new types of interconnections called “virtual private interconnections”), and discuss their wide-ranging implications for obtaining an accurate and comprehensive map of the Internet's interconnection fabric.

The most-followed Twitter users and their pairwise relationships form a sub-graph of all Twitter users that we call the Twitter elite network. The connectivity patterns and influence (in terms of reply and retweet activity) among these elite users illustrate how the “important” users connect and interact with one another on Twitter. Such an elite-focused view also provides valuable information about the structure of the Twitter network as a whole. This paper presents the first detailed characterization of the top-10K Twitter elite network. We describe a new technique to efficiently and accurately capture the Twitter elite network along with social attributes of individual elite accounts. We show that a sufficiently large elite network is typically composed of 15-20 resilient and socially cohesive communities representing “socially meaningful” components of the elite network. We then characterize the community-level structure of the elite network in terms of bias in directed pairwise connectivity and relative reachability. We demonstrate that both the retweet and reply activity between elite users are effectively contained within individual elite communities. Finally, we illustrate that a majority of the elite friends of regular Twitter users tend to belong to a single elite community. This finding offers a promising criterion to group regular users into “shadow partitions” based on their association with elite communities. We show that the level of overall inter-connectivity between shadow partitions mirrors the inter-connectivity of the elite communities. This suggests that these shadow partitions can be viewed as extensions of their corresponding elite communities.

In the era when Facebook and Twitter dominate the market for social media, Google has introduced Google+ (G+) and reported a significant growth in its size while others called it a ghost town. This begs the question of whether G+ can really attract a significant number of connected and active users despite the dominance of Facebook and Twitter. This paper presents a detailed longitudinal characterization of G+ based on large-scale measurements. We identify the main components of G+ structure and characterize the key feature of their users and their evolution over time. We then conduct detailed analysis on the evolution of connectivity and activity among users in the largest connected component (LCC) of G+ structure, and compare their characteristics to other major online social networks (OSNs). We show that despite the dramatic growth in the size of G+, the relative size of the LCC has been decreasing and its connectivity has become less clustered. While the aggregate user activity has gradually increased, only a very small fraction of users exhibit any type of activity, and an even smaller fraction of these users attracts any reaction. The identity of users with most followers and reactions reveal that most of them are related to high-tech industry. To our knowledge, this study offers the most comprehensive characterization of G+ based on the largest collected datasets.

In the era when Facebook and Twitter dominate the market for social media, Google has introduced Google+ (G+) and reported a significant growth in its size while others called it a ghost town. This begs the question that "whether G+ can really attract a significant number of connected and active users despite the dominance of Facebook and Twitter?".