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In this paper, we study the posting behavior of OSN users, in particular the posting frequency and temporal patterns, and consider possible interpretations of how users use the platform. At the aggregate (macro) level, we find two distinct peaks, one during morning working hours, and one in the evening. The morning peak is more pronounced for frequent posters, while the evening peak is pronounced in the remaining users. We postulate that this difference results from qualitatively different usage of the OSN platform (e.g. for work, with customers, etc.) than purely social interactions (e.g., friends, family, etc.). We also study user posting behavior at an individual (micro) level and apply LDA to cluster user temporal patterns, interpret our results. Our study provides possibly new insights into user activity in today's OSNs, and suggests a framework for profiling users based on their posting activities. In the process, we provide a novel application of LDA, to temporal user posting behavior by equating the time epochs of posts to words in documents. We believe our approach will complement other methods of user profiling based on static demographic information and friendship network information.

Citations serve as an important metric for identifying experts and opinion leaders in academic communities. In this paper, we analyze the evolution of yearly rankings of top-cited (C-list) authors in the domain of Computer Science. In searching for factors that help authors become top-cited, we also gather authors in the top-collaboration list (A-list) and top-publication list (P-list) for each year, and analyze cross-correlation of the C-list with the corresponding A-list and P-list for each year. Results show that the A-list and P-list serve as (unreliable) indicators for appearance on the C-list, but their effect is quick and short-lived. Through further case studies we find other key factors, such as the seminal importance of an author's publication and the association on an author's work with hot topic trends, may significantly affect rank dynamics. Based on the study of citation rank dynamics in academia, we then discuss the modeling of rank dynamics, specifically a model based on item visibility and item strength, and the general applicability of such a model.

Internet service providers (ISPs) depend on one another to provide global network services. However, the profit-seeking nature of the ISPs leads to selfish behaviors that result in inefficiencies and disputes in the network. This concern is at the heart of the "network neutrality" debate, which also asks for an appropriate compensation structure that satisfies all types of ISPs. Our previous work showed in a general network model that the Shapley value has several desirable properties, and that if applied as the revenue model, selfish ISPs would yield globally optimal routing and interconnecting decisions.In this paper, we use a more detailed and realistic network model with three classes of ISPs: content, transit, and eyeball. This additional detail enables us to delve much deeper into the implications of a Shapley settlement mechanism. We derive closed-form Shapley values for more structured ISP topologies and develop a dynamic programming procedure to compute the Shapley revenues under more diverse Internet topologies. We also identify the implications on the bilateral compensation between ISPs and the pricing structures for differentiated services. In practice, these results provide guidelines for solving disputes between ISPs and for establishing regulatory protocols for differentiated services and the industry.

Within the current Internet, autonomous ISPs implement bilateral agreements, with each ISP establishing agreements that suit its own local objective to maximize its profit. Peering agreements based on local views and bilateral settlements, while expedient, encourage selfish routing strategies and discriminatory interconnections. From a more global perspective, such settlements reduce aggregate profits, limit the stability of routes, and discourage potentially useful peering/connectivity arrangements, thereby unnecessarily balkanizing the Internet. We show that if the distribution of profits is enforced at a global level, then there exist profit-sharing mechanisms derived from the coalition games concept of Shapley value and its extensions that will encourage these selfish ISPs who seek to maximize their own profits to converge to a Nash equilibrium. We show that these profit-sharing schemes exhibit several fairness properties that support the argument that this distribution of profits is desirable. In addition, at the Nash equilibrium point, the routing and connecting/peering strategies maximize aggregate network profits and encourage ISP connectivity so as to limit balkanization.

In this paper we outline a general methodology illustrated by specific examples for the optimal interpretation of a class of semi-join queries in distributed database systems.