Adjustable reach in a network centrality based on current flows

Centrality, which quantifies the "importance" of individual nodes, is among the most essential concepts in modern network theory. Most prominent centrality measures can be expressed as an aggregation of influence flows between pairs of nodes. As there are many ways in which influence can be defined, many different centrality measures are in use. Parametrized centralities allow further flexibility and utility by tuning the centrality calculation to the regime most appropriate for a given network. Here, we identify two categories of centrality parameters. Reach parameters control the attenuation of influence flows between distant nodes. Grasp parameters control the centrality's potential to send influence flows along multiple, often nongeodesic paths. Combining these categories with Borgatti's centrality types [S. P. Borgatti, Social Networks 27, 55-71 (2005)], we arrive at a novel classification system for parametrized centralities. Using this classification, we identify the notable absence of any centrality measures that are radial, reach parametrized, and based on acyclic, conservative flows of influence. We therefore introduce the ground-current centrality, which is a measure of precisely this type. Because of its unique position in the taxonomy, the ground-current centrality has significant advantages over similar centralities. We demonstrate that, compared to other conserved-flow centralities, it has a simpler mathematical description. Compared to other reach centralities, it robustly preserves an intuitive rank ordering across a wide range of network architectures. We also show that it produces a consistent distribution of centrality values among the nodes, neither trivially equally spread (delocalization), nor overly focused on a few nodes (localization). Other reach centralities exhibit both of these behaviors on regular networks and hub networks, respectively

IMPACT 2002+: A new life cycle impact assessment methodology

The new IMPACT 2002+ life cycle impact assessment methodology proposes a feasible implementation of a combined midpoint/damage approach, linking all types of life cycle inventory results (elementary flows and other interventions) via 14 midpoint categories to four damage categories. For IMPACT 2002+, new concepts and methods have been developed, especially for the comparative assessment of human toxicity and ecotoxicity. Human Damage Factors are calculated for carcinogens and non-carcinogens, employing intake fractions, best estimates of dose-response slope factors, as well as severities. The transfer of contaminants into the human food is no more based on consumption surveys, but accounts for agricultural and livestock production levels. Indoor and outdoor air emissions can be compared and the intermittent character of rainfall is considered. Both human toxicity and ecotoxicity effect factors are based on mean responses rather than on conservative assumptions. Other midpoint categories are adapted from existing characterizing methods (Eco-indicator 99 and CML 2002). All midpoint scores are expressed in units of a reference substance and related to the four damage categories human health, ecosystem quality, climate change, and resources. Normalization can be performed either at midpoint or at damage level. The IMPACT 2002+ method presently provides characterization factors for almost 1500 different LCI-results, which can be downloaded at http://www.epfl.ch/impac

Simulating acculturation dynamics between migrants and locals in relation to network formation

International migration implies the coexistence of different ethnic and cultural groups in the receiving country. The refugee crisis of 2015 has resulted in critical levels of opinion polarization on the question of whether to welcome migrants, causing clashes in receiving countries. This scenario emphasizes the need to better understand the dynamics of mutual adaptation between locals and migrants, and the conditions that favor successful integration. Agent-based simulations can help achieve this goal. In this work, we introduce our model MigrAgent and our preliminary results. The model synthesizes the dynamics of migration intake and post-migration adaptation. It explores the different acculturation outcomes that can emerge from the mutual adaptation of a migrant population and a local population depending on their degree of tolerance. With parameter sweeping, we detect how different acculturation strategies can coexist in a society and in different degrees among various subgroups. The results show higher polarization effects between a local population and a migrant population for fast intake conditions. When migrant intake is slow, transitory conditions between acculturation outcomes emerge for subgroups, e.g., from assimilation to integration for liberal migrants and from marginalization to separation for conservative migrants. Relative group sizes due to speed of intake cause counterintuitive scenarios, such as the separation of liberal locals. We qualitatively compare the processes of our model with the German portion sample of the survey Causes and Consequences of Socio-Cultural Integration Processes among New Immigrants in Europe (SCIP), finding preliminary confirmation of our assumptions and results.Comment: 24 pages, plus supplemental material, 11 figure

Illuminating an Ecosystem of Partisan Websites

This paper aims to shed light on alternative news media ecosystems that are believed to have influenced opinions and beliefs by false and/or biased news reporting during the 2016 US Presidential Elections. We examine a large, professionally curated list of 668 hyper-partisan websites and their corresponding Facebook pages, and identify key characteristics that mediate the traffic flow within this ecosystem. We uncover a pattern of new websites being established in the run up to the elections, and abandoned after. Such websites form an ecosystem, creating links from one website to another, and by `liking' each others' Facebook pages. These practices are highly effective in directing user traffic internally within the ecosystem in a highly partisan manner, with right-leaning sites linking to and liking other right-leaning sites and similarly left-leaning sites linking to other sites on the left, thus forming a filter bubble amongst news producers similar to the filter bubble which has been widely observed among consumers of partisan news. Whereas there is activity along both left- and right-leaning sites, right-leaning sites are more evolved, accounting for a disproportionate number of abandoned websites and partisan internal links. We also examine demographic characteristics of consumers of hyper-partisan news and find that some of the more populous demographic groups in the US tend to be consumers of more right-leaning sites.Comment: Published at The Web Conference 2018 (WWW 2018). Please cite the WWW versio

Per capita income and the extensive margin of bilateral trade

This paper quantitatively explores the role of the demand structure in explaining the relationship between an importer's per capita income and the extensive margin of bilateral trade. The underlying mechanism is based on the fact that agents expand the set of goods they consume with income. This in turn affects the structure of a country's import demand and therewith the extensive margin of trade. We formalize this intuition by incorporating preferences that allow for binding non-negativity constraints into an otherwise standard Ricardian multi-country model. We quantify the model using the data on US consumer expenditures and aggregate values of bilateral trade flows and find that the behavior of the model's extensive margin of bilateral trade is consistent with the data (as opposed to the standard model). Two popular counterfactual experiments - lower trade costs and the rise of China and India - demonstrate that the mechanism outlined in this paper is indeed quantitatively important

The Economic Case for Landscape Restoration in Latin America

Degraded lands—lands that have lost some degree of their natural productivity through human activity—account for over 20 percent of forest and agricultural lands in Latin America and the Caribbean. Some 300 million hectares of the region's forests are considered degraded, and about 350 million hectares are now classified as deforested. The agriculture and forestry sectors are growing and exerting great pressure on natural areas. With the region expected to play an increasingly important role in global food security, this pressure will continue to ratchet up. In addition, land degradation is a major driver in greenhouse gas emissions in the region. Forest and landscape restoration can offer a solution to these increasing pressures

Assessing the potential for U.S. utility green bonds

EXECUTIVE SUMMARY: Bonds are the largest single class of financial instrument across the world’s financial markets. Recently, a subclass of these bonds, called green bonds, has emerged in the market place. Green bonds are a type of bond whose proceeds may be used only for certain approved “green” investments. In exchange for agreeing to invest only in such projects, the bond issuer obtains some value greater than they would obtain from traditional financing, and are therefore encouraged to finance and undertake a greater number of green projects. This unique value may not be recognized in traditional financial accounting. Of course, like any other capital-raising investment, green bonds enable their issuer to finance a new project that should increase (or at least maintain) its revenues, profits, and cash flow. The utility sector was the second largest issuer of green bonds in 2017, accounting for $26.2 billion dollars’ worth of green bond issuance globally. These were primarily issued to finance renewable energy projects, a class of projects that makes the utility sector one of the most logical for deployment of green bonds. While choosing to issue green bonds does not seem to have any price advantage over regular bonds in the market, green bonds can provide other benefits. These benefits may include reputation effects, better treatment in secondary markets, and other intangibles (See Table ES1)