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Talk pages play a fundamental role in Wikipedia as the place for discussion and communication. In this work we use the comments on these pages to extract and study three networks, corresponding to different kinds of interactions. We find evidence of a specific assortativity profile which differentiates article discussions from personal conversations. An… (More)

- David Flatow, Mor Naaman, Ke Eddie Xie, Yana Volkovich, Yaron Kanza
- WSDM
- 2015

Social media users share billions of items per year, only a small fraction of which is geotagged. We present a data-driven approach for identifying non-geotagged content items that can be associated with a hyper-local geographic area by modeling the location distributions of n-grams that appear in the text. We explore the trade-off between accuracy and… (More)

Core decomposition has proven to be a useful primitive for a wide range of graph analyses. One of its most appealing features is that, unlike other notions of dense subgraphs, it can be computed linearly in the size of the input graph. In this paper we provide an analogous tool for uncertain graphs, i.e., graphs whose edges are assigned a probability of… (More)

Personalized PageRank is used in Web search as an importance measure for Web documents. The goal of this paper is to characterize the tail behavior of the PageRank distribution in the Web and other complex networks characterized by power laws. To this end, we model the PageRank as a solution of a stochastic equation R d = ∑ N i=1 AiRi + B, where Ri’s are… (More)

- Pablo Aragón, David Laniado, Andreas Kaltenbrunner, Yana Volkovich
- WikiSym
- 2012

It is arguable whether history is made by great men and women or vice versa, but undoubtably social connections shape history. Analysing Wikipedia, a global collective memory place, we aim to understand how social links are recorded across cultures. Starting with the set of biographies in the English Wikipedia we focus on the networks of links between these… (More)

- Andreas Kaltenbrunner, Salvatore Scellato, +4 authors Cecilia Mascolo
- WOSN
- 2012

Online friendship connections are often not representative of social relationships or shared interest between users, but merely provide a public display of personal identity. A better picture of online social behaviour can be achieved by taking into account the intensity of communication levels between users, yielding useful insights for service providers… (More)

- Yana Volkovich, Nelly Litvak, Debora Donato
- WAW
- 2007

We study the relation between PageRank and other parameters of information networks such as in-degree, out-degree, and the fraction of dangling nodes. We model this relation through a stochastic equation inspired by the original definition of PageRank. Further, we use the theory of regular variation to prove that PageRank and in-degree follow power laws… (More)

OUTLINE • Power laws in complex networks • Model for power law distribution of PageRank importance scores • Dependence between power law graph parameters, angular measure • Analytical derivations for the angular measure X is regularly varying random variable with index α if P(X>x) ~ L(x)x-α as x → ∞ (here a~b if a/b →1) L(x) is slowly varying if for every… (More)

The popularity of theWeb has allowed individuals to communicate and interact with each other on a global scale: people connect both to close friends and acquaintances, creating ties that can bridge otherwise separated groups of people. Recent evidence suggests that spatial distance is still affecting social links established on online platforms, with online… (More)

- Nelly Litvak, Werner R. W. Scheinhardt, Yana Volkovich
- Internet Mathematics
- 2007

PageRank is a popularity measure designed by Google to rank Web pages. Experiments confirm that PageRank values obey a power law with the same exponent as In-Degree values. This paper presents a novel mathematical model that explains this phenomenon. The relation between PageRank and In-Degree is modeled through a stochastic equation, which is inspired by… (More)