Activity ageing in growing networks

We present a model for growing information networks where the ageing of a node depends on the time at which it entered the network and on the last time it was cited. The model is shown to undergo a transition from a small-world to large-world network. The degree distribution may exhibit very different shapes depending on the model parameters, e.g. delta-peaked, exponential or power-law tailed distributions.Comment: 9 pages, 2 figure

Fracture-controlled gas hydrate systems in the northern Gulf of Mexico

High-angle, open mode fractures control the presence of natural gas hydrate in water-saturated clays at the Keathley Canyon 151 site in the northern Gulf of Mexico, which was investigated for gas hydrates as part of the Chevron Joint Industry Project drilling in 2005. We analyze logging-while-drilling resistivity images and infer that gas hydrate accumulated in situ in two modes: filling fractures and saturating permeable beds. High-angle hydrate-filled fractures are the most common mode for gas hydrate occurrence at this site, with most of these fractures dipping at angles of more than 40° and occurring between 220 and 300 m below seafloor. These fractures all strike approximately N–S, which agrees with the 165°SE–345°NW maximum horizontal stress direction determined from borehole breakouts and which aligns with local bathymetric contours. In one interval of hydrate-filled fractures, porosity increases with increasing hydrate saturation. We suggest that high pore pressure may have dilated sediments during fracture formation, causing this increase in porosity. Furthermore, the formation of gas hydrate may have heaved fractures apart, also increasing the formation porosity in this interval

Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search

We present a framework for quantifying and mitigating algorithmic bias in mechanisms designed for ranking individuals, typically used as part of web-scale search and recommendation systems. We first propose complementary measures to quantify bias with respect to protected attributes such as gender and age. We then present algorithms for computing fairness-aware re-ranking of results. For a given search or recommendation task, our algorithms seek to achieve a desired distribution of top ranked results with respect to one or more protected attributes. We show that such a framework can be tailored to achieve fairness criteria such as equality of opportunity and demographic parity depending on the choice of the desired distribution. We evaluate the proposed algorithms via extensive simulations over different parameter choices, and study the effect of fairness-aware ranking on both bias and utility measures. We finally present the online A/B testing results from applying our framework towards representative ranking in LinkedIn Talent Search, and discuss the lessons learned in practice. Our approach resulted in tremendous improvement in the fairness metrics (nearly three fold increase in the number of search queries with representative results) without affecting the business metrics, which paved the way for deployment to 100% of LinkedIn Recruiter users worldwide. Ours is the first large-scale deployed framework for ensuring fairness in the hiring domain, with the potential positive impact for more than 630M LinkedIn members.Comment: This paper has been accepted for publication at ACM KDD 201

Log-Networks

We introduce a growing network model in which a new node attaches to a randomly-selected node, as well as to all ancestors of the target node. This mechanism produces a sparse, ultra-small network where the average node degree grows logarithmically with network size while the network diameter equals 2. We determine basic geometrical network properties, such as the size dependence of the number of links and the in- and out-degree distributions. We also compare our predictions with real networks where the node degree also grows slowly with time -- the Internet and the citation network of all Physical Review papers.Comment: 7 pages, 6 figures, 2-column revtex4 format. Version 2: minor changes in response to referee comments and to another proofreading; final version for PR

Information Horizons in Networks

We investigate and quantify the interplay between topology and ability to send specific signals in complex networks. We find that in a majority of investigated real-world networks the ability to communicate is favored by the network topology on small distances, but disfavored at larger distances. We further discuss how the ability to locate specific nodes can be improved if information associated to the overall traffic in the network is available.Comment: Submitted top PR

Degree distributions of growing networks

The in-degree and out-degree distributions of a growing network model are determined. The in-degree is the number of incoming links to a given node (and vice versa for out-degree. The network is built by (i) creation of new nodes which each immediately attach to a pre-existing node, and (ii) creation of new links between pre-existing nodes. This process naturally generates correlated in- and out-degree distributions. When the node and link creation rates are linear functions of node degree, these distributions exhibit distinct power-law forms. By tuning the parameters in these rates to reasonable values, exponents which agree with those of the web graph are obtained

Asymptotic behavior of the Kleinberg model

We study Kleinberg navigation (the search of a target in a d-dimensional lattice, where each site is connected to one other random site at distance r, with probability proportional to r^{-a}) by means of an exact master equation for the process. We show that the asymptotic scaling behavior for the delivery time T to a target at distance L scales as (ln L)^2 when a=d, and otherwise as L^x, with x=(d-a)/(d+1-a) for ad+1. These values of x exceed the rigorous lower-bounds established by Kleinberg. We also address the situation where there is a finite probability for the message to get lost along its way and find short delivery times (conditioned upon arrival) for a wide range of a's

Small world yields the most effective information spreading

Spreading dynamics of information and diseases are usually analyzed by using a unified framework and analogous models. In this paper, we propose a model to emphasize the essential difference between information spreading and epidemic spreading, where the memory effects, the social reinforcement and the non-redundancy of contacts are taken into account. Under certain conditions, the information spreads faster and broader in regular networks than in random networks, which to some extent supports the recent experimental observation of spreading in online society [D. Centola, Science {\bf 329}, 1194 (2010)]. At the same time, simulation result indicates that the random networks tend to be favorable for effective spreading when the network size increases. This challenges the validity of the above-mentioned experiment for large-scale systems. More significantly, we show that the spreading effectiveness can be sharply enhanced by introducing a little randomness into the regular structure, namely the small-world networks yield the most effective information spreading. Our work provides insights to the understanding of the role of local clustering in information spreading.Comment: 6 pages, 7 figures, accepted by New J. Phy

Two-dimensional ranking of Wikipedia articles

The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists {\it ab aeterno}. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.Comment: RevTex 9 pages, data, discussion added, more data at http://www.quantware.ups-tlse.fr/QWLIB/2drankwikipedia

The Emergence of Informal Institutions among Internal Migrants in Urban China

China’s dramatic economic development and urbanisation have led to an increase in its number of internal migrants. As of 2013, this group accounted for more than 20 per cent of the country’s population, and approximately 70 per cent of people in this group are working in the informal economy. This paper pays special attention to migrant-traders in the informal sector and the strategies they use in Shanghai. Migrants are doubly marginalised by the hukou (户口) and danwei (单位) systems in the megacity and have only limited access to social welfare. It is argued that the informal strategies of these marginalised actors develop in related patterns of social relationships and institutional constraints. Such strategies create new forms of informal institutions that are justified and gain legitimacy when countering unequal and hierarchical formal institutions and social arrangements. This paper empirically explores how informal institutions can act in parallel with or diverge from formal institutions, and how they might influence formal institutions in the long term