As crowd-sourced curation of news and information become the norm, it is important to understand not only how individuals consume information through social news Web sites, but also how they contribute to their ranking systems. In the present work, we introduce and make available a new dataset containing the activity logs that recorded all activity for 309 Reddit users for one year. Using this newly collected data, we present findings that highlight the browsing and voting behavior of the study's participants. We find that most users do not read the article that they vote on, and that, in total, 73% of posts were rated (i.e., upvoted or downvoted) without first viewing the content. We also show evidence of cognitive fatigue in the browsing sessions of users that are most likely to vote.

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In graph theory the diameter is an important topological metric for understanding size and density of a graph. Unfortunately, the graph diameter is computationally difficult to measure for even moderately-sized graphs, insomuch that approximation algorithms are commonly used instead of exact measurements. In this paper, we present a new algorithm to measure the exact diameter of unweighted graphs using vertex programming, which is easily distributed. We also show the practical performance of the algorithm in comparison to other, widely available algorithms and implementations, as well as the unreliability in accuracy of some pseudo-diameter estimators.

Patterns often appear in a variety of large, real-world networks, and interesting physical phenomena are often explained by network topology as in the case of the bow-tie structure of the World Wide Web, or the small world phenomenon in social networks. The discovery and modelling of such regular patterns has a wide application from disease propagation to financial markets. In this work we describe a newly discovered regularly occurring striation pattern found in the PageRank ordering of adjacency matrices that encode real-world networks. We demonstrate that these striations are the result of well-known graph generation processes resulting in regularities that are manifest in the typical neighborhood distribution. The spectral view explored in this paper encodes a tremendous amount about the explicit and implicit topology of a given network, so we also discuss the interesting network properties, outliers and anomalies that a viewer can determine from a brief look at the re-ordered matrix.

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