[show abstract][hide abstract] ABSTRACT: The notion of the ‘productivity puzzle,’ referring particularly to gender disparities in science and technology publication rates, raises a variety of critical issues for understanding related workforce development and capacity. However, such issues typically are framed relative to an increasingly outdated cultural and technological landscape in which scientific productivity is viewed principally as an outcome. We argue instead that characterizing scientific productivity as a multifaceted dynamic, highly networked, and interactive process, rather than just an outcome, might provide greater insight into the gendered nature of science and lead to a re-framing of the gender-differentiated productivity puzzle. By rethinking how we engage related questions, we might gain ground on explaining and unraveling the productivity puzzle in ways that will benefit the scientific enterprise and society in general.
[show abstract][hide abstract] ABSTRACT: Context: Online social networks and the Web 2.0 technologies embedded in these sites are creating an environment in which individuals can communicate and share information in ways that were previously not possible. Such websites are providing an unprecedented and growing collection of data on individual behavior that is very rich in detail. This includes information on with whom, when and where people interact, and more generally, what their activity patterns look like in time and space, and even what their sentiment or preferences are at specific moments and locations. Knowledge Gaps: There is a burgeoning body of literature that draws upon social media data and more broadly information collected via mobile communications devices (e.g., cell phone trajectories) to model and understand particular aspects of human behavior, including mobility patterns and social and spatio-temporal interaction. Yet, very little of this research has examined how and to what extent the spatio-temporal activity patterns revealed by these new forms of data vary across metropolitan areas, especially after controlling for relevant city-specific characteristics such as the size, density, composition or demographic profile of a city. While we recognize that the study of space-time activity patterns itself is not new, there are some gaps in the literature that should be noted. First, most analyses have been confined to a select set of cities – i.e., those that have conducted travel diaries or activity-based surveys. Due to inconsistencies in the format and type of information collected from such surveys, comparative analyses are problematic. Second, few studies have looked explicitly at the simultaneous integration of space, time and social (inclusive of cyber socialization) interaction, and the complex mobility patterns that arise from this behavior. Lastly, unlike location sharing services data, the information provided by travel behavior surveys tend to capture only mobility patterns arising from the primary residents of a city and not the behavior of transient visitors to that location. Study Objectives: The primary objectives of this study are to 1). understand how and to what extent location sharing services data approximate regional spatio-temporal activity patterns 2). develop a set of network-based metrics for characterizing the centrality and disorder of such activities in a region, and, 3). conduct a cross-city comparison using these metrics and related indicators of mobility.Data: To carry out the proposed research, we intend to use location services data collected over a five month period in 2010-11 (Cheng et al., 2011). This data provides information on user check-ins, or more specifically, where individuals indicate they are at different times of the day and week. Additional details on each individual’s status within the social networks that they belong are also included in the dataset. Methodology: The study methodology draws heavily on techniques from social network analysis, although concepts form landscape ecology, physics and geography are also utilized to capture different aspects of regional activity patterns. To gain an understanding of the types of activities that location sharing services data capture, we first conduct a correlation analysis using sector-based establishment data from the U.S. Census County Business Patterns. Correlations are examined at the zip code level. Second, using a space-time bipartite network topology, we derive a set of measures that characterize the centrality and disorder (entropy) of activities in a region, and that further can be decomposed to examine the spatial distribution of these characteristics. With individual location data aggregated to grid cells and summarized according to regular time intervals, we apply the technique to two U.S. metropolitan areas: Atlanta and Chicago.Significance: Implications for travel demand forecasting, epidemiological and information diffusion modelling and abnormal crowd detection (e.g., through “burstiness” analysis) will be drawn from the study.
[show abstract][hide abstract] ABSTRACT: Acknowledging that the digital divide is becoming more of a knowledge divide, we invoke an image of the 'Tower of Babel,' evincing a vertical hierarchy of information and relations in which access to the top tiers is highly limited. Depicting the knowledge society itself, which encompasses a highly complex interconnected system of digital networks within which interaction among social actors occur and from which knowledge is created and diffused, we emphasize networks as a central factor determining access and posit the broader notion of then Digital Knowledge Network Divide (DKND) to better understand related structures and dynamics. In the face of concerns over democratizing trends and, more, general calls for expanding the science and technology workforce and increasing scientific literacy, access to knowledge is critical. Accordingly, an important challenge for the years to come will be to characterize the evolving and unique landscape of the knowledge society in order to inform and design effective policies and programs. Related research will require the development of measures and tools that capture the hierarchical relations and dynamics of the DKND and that, ultimately, will allow for the assessment of related spatio-temporal disparities and the determination of indicators of network connectivity to measure changes in overall access and participation in the knowledge society.
[show abstract][hide abstract] ABSTRACT: This article presents an analysis of five available house price indices that are used to track house prices at the metropolitan area level. These five indices are (1) the Federal Housing Finance Agency (FHFA) House Price Index (HPI), (2) the Standard & Poor’s/Case-Shiller® Home Price Indices, (3) an adjusted version of the FHFA House Price Index, (4) the Zillow Home Value Index, and (5) the NATIONAL ASSOCIATION OF REALTORS® Median Home Price. This study first discusses the strengths and weaknesses of these indices for use in a spatio-temporal analysis. Then, it provides a comparative analysis of their change rate for 10 metropolitan statistical areas (MSAs) for two time periods: the third quarter of 2006 through the third quarter of 2007 and the first quarter of 2007 through the first quarter of 2008. In addition, this research constructs a series of spatio-temporal indicators based on time and spatial lags of the HPI for 302 MSAs for the 2000 to 2007 period. The results of this data brief could help researchers interested in spatio-temporal analyses of the latest housing bubble and of house price indices at large.
[show abstract][hide abstract] ABSTRACT: Foreclosures are spatially contagious by nature (Can 1998). Abandoned or vacant properties have a negative spillover effect, by reducing the expected return on investment on surrounding properties. While there is a growing body of literature focusing on the latest wave of foreclosures in the US (Foote, Gerardi and Willen 2008b; Coulton et al. 2008; Lin et al. 2009), the spatial aspect has not been analyzed. We explore the spatial contagion of foreclosures, at the neighborhood level. Following an epidemiological concept, we define foreclosure contagion as an increase in neighborhood foreclosures that spreads over time from neighborhood to adjoining neighborhoods. In addition, we define foreclosure hotspots as areas with high values of foreclosures that are surrounded by areas with high foreclosure levels. The purpose is to identify the evolution of this spatial phenomenon by structure type (single units versus multi-units) and the socio-demographic characteristics of the neighborhoods affected by foreclosure. This research employs data from the Warren Group on nearly 15, 000 residential properties that entered the second stage of the foreclosure process during 2007 and the first quarter of 2008. The data cover four states: Connecticut, Massachusetts, New Hampshire, and Rhode Island. Our empirical evidence shows that the foreclosures in New England during this time period exhibited a spatial contagion pattern and that most troubled neighborhoods, the foreclosure hotspots, were “infecting” the adjacent neighborhoods. Any foreclosure mitigation program should include a spatial focus and target the foreclosures in the foreclosure hotspots.
[show abstract][hide abstract] ABSTRACT: Epistemic communities have been identified and studied through collaboration and citation analyses. One issue that has received increasing calls for research in this area is the role of gender, especially in light of significant variation in participation and productivity along gender lines. Accordingly, we argue for the active incorporation of gender as a central consideration in analyses aimed at assessing epistemic communities and their impact at individual, national, and international levels of analysis. Drawing on various theoretical perspectives and considering a range of empirical findings, directions for research are delineated for assessing gender differentiation in collaboration productivity and network participation, particularly in terms of scientific discipline, institutional referents, and professional age and status, along with socio-cultural and political characteristics. The development of gender-specific metrics at different levels of aggregation and their broader analytical incorporation are discussed relative to assessments of gender distributional inequities and network properties. We suggest that allowing for various factors dictated by individual circumstances and field and network conditions can lead to improved contextual consideration and help to fill gaps in our knowledge to provide better and more informed understandings about the productivity and career patterns of women scientists.
[show abstract][hide abstract] ABSTRACT: In this paper we develop an exploratory non-parametric clustering model of spatial and/or spatio-temporal phenomena based on Kolmogorov entropy. The methodology will be tested using quarterly HPI (Housing Price Index) data for 350 plus cities in the US from the Federal Financing and Housing Administration (FHFA), an agency of HUD (US Dept of Housing and Urban Development). This multivariate data will be also analyzed with Principal Component Analysis (PCA) techniques to identify key regions involved in creating the housing bubble and its spread to the rest of cities.
[show abstract][hide abstract] ABSTRACT: In this paper we explore the development of a parameter free region classifier based on Kolmogorov complexity. Given a set of regions described by unlimited but fixed number of attributes for each region, the region classifier will be able to build a classification tree which will help identify which regions are similar/dissimilar to each other based on a relative distance measure derived from Kolmogorov complexity. The region classifier is tested with the block level US Census demographics data as well as hitech establishment data for a subset of metropolitan regions. Preliminary results are presented for the census data as well as for the hitech sector for three different time periods.
[show abstract][hide abstract] ABSTRACT: The events of 9/11 brought renewed focus to critical infrastructure, but the security of infrastructure has been and continues
to be an issue outside the scope of any one event or country. Oil pipeline attacks in Iraq, massive blackouts in Italy, the
United States, and Russia, submarine cable failures in the Atlantic, accidental and intentional failures of infrastructure
are an increasing and complex problem. The issue of infrastructure security is a global problem both is applicability and
connectivity. All nations are dependent on infrastructure and many of these infrastructures cross international borders and
some span the globe. A problem facing all nations is that they have the responsibility for securing infrastructure but critical
aspects are owned by the private sector. This though is only one of many problems facing infrastructure security: 1) infrastructures
are interdependent on each others reliability 2) infrastructures are large, dynamically unsynchronized, and complex 3) sharing
information about infrastructure vulnerabilities is severely hampered by fears of regulation and competition. Along with these
direct obstacles there are larger economic forces that complicate the issue. The markets driving infrastructure are geared
towards maximizing efficiency to increase profit and not maximizing protection, which can result in public vulnerabilities.
[show abstract][hide abstract] ABSTRACT: Disruptions to transportation networks can be very costly. However, managing disruptions and the costs associated with these
events, poses some challenges. Transport networks are, in many cases, large and complex. This paper develops a method, based
on complex network theory, to analyse transportation networks. It provides a way, through the use raster-based geographic
information system (GIS) techniques, to identify critical nodes or links in a network that reflect spatial interdependencies
with other networks and to assess how resilient the networks are to failures of these locations. For purposes of illustration,
the method is applied to the network of major roads and rail in the State of Florida.
Networks and Spatial Economics 01/2007; 7(4):301-313. · 1.23 Impact Factor
[show abstract][hide abstract] ABSTRACT: Designing resilient and reliable networks is a principle concern of planners and private firms. Traffic congestion whether recurring or as the result of some aperiodic event is extremely costly. This paper describes an alternative process and a model for analyzing the resiliency of networks that address some of the shortcomings of more traditional approaches â€“ e.g., the four-step modeling process used in transportation planning. It should be noted that the authors do not view this as a replacement to current approaches but rather as a complementary tool designed to augment analysis capabilities. The process that is described in this paper for analyzing the resiliency of a network involves at least three steps: 1. assessment or identification of important nodes and links according to different criteria 2. verification of critical nodes and links based on failure simulations and 3. consequence. Raster analysis, graph-theory principles and GIS are used to develop a model for carrying out each of these steps. The methods are demonstrated using two, large interdependent networks for a metropolitan area in the United States.
European Regional Science Association, ERSA conference papers. 01/2006;
[show abstract][hide abstract] ABSTRACT: This paper examines small-world phenomena in communications systems focusing specifically on three networks each operating in different geographical spheres. The first is the logical IP (Internet Protocol) fibre optic infrastructure that connects major metropolitan areas in the United States (for the years 1997 through 2000), the second a portion of the Italian phone network using outgoing landline calls by district to capture network traffic dynamics, while the third one is a Peer-to-Peer (P2P) data network for the international exchange of music for a particular group of independent people. Power-law distributions are generated for each network to look for scale-free properties. The implications of the results of these experiments for transportation policy and planning, and the way in which they may vary depending on geography – i.e., for example, whether or not a network operates in Europe versus the United States, or whether it is one with no geographical boundaries and rather an international dimension – are hypothesized although a more thorough investigation of this is warranted. Also the paper offers some thoughts about the analytical methodologies, visualization techniques and data that are needed to facilitate a valid and informative cross-Atlantic comparison of communications networks in this context.
[show abstract][hide abstract] ABSTRACT: Cybersecurity is an issue of increasing concern since the events of September 11 . Many questions have been raised concerning the security of the Internet and the rest of US's information infrastructure. This paper begins to examine the issue by analyzing the Internet's autonomous system (AS) map. Using the AS map, generic malicious infections are simulated and different defense strategies are considered in a cost effectiveness analysis framework. The results show that protecting the most connected nodes provides significant gains in security and that after the small minority of the most connected nodes are protected there are diminishing returns for further protection.
[show abstract][hide abstract] ABSTRACT: In light of the rise of malicious attacks on the Internet, and the various networks and applications attached to it, new approaches towards modeling predatory activity in networks could be useful. Past research has simulated networks assuming that all vertices are homogenously susceptible to attack or infection. Often times in real world networks only subsets of vertices are susceptible to attack or infection in a heterogeneous population of vertices. One approach to examining a heterogeneous network susceptible to attack is modeling a network as a predator prey landscape. If each type of vulnerable device is considered a heterogeneous species what level of species diversification is needed to keep a malicious attack from a causing a catastrophic failure to the entire network. This paper explores the predator prey analogy for the Internet and presents findings on how different levels of species diversification effects network resilience. The paper will also discuss the connection between diversification, competition, anti-trust, and national security.
[show abstract][hide abstract] ABSTRACT: In light of the rise of malicious attacks on the Internet and the various networks and applications attached to it, new approaches towards modeling predatory activity in networks is called for. Past research has simulated networks assuming that all nodes are homogenously susceptible to attack or infection. Often times in real world networks only subsets of nodes are susceptible attack or infection in a heterogeneous population of nodes. One approach to examining a heterogeneous network susceptible to attack is modeling cyberspace as a predator prey landscape. If each type of vulnerable device is considered a heterogeneous species what level of species diversification is needed to keep a malicious attack from a causing a catastrophic failure to the entire network. This paper explores the predator prey analogy for the Internet and presents findings on how different levels of species diversification effects network resilience. The paper will also discuss the connection between diversification, competition, anti-trust, and national security.
[show abstract][hide abstract] ABSTRACT: The events of 9/11 brought an increased focus on security in the United States and specifically the protection of critical infrastructure. Critical infrastructure encompasses a wide array of critical assets such as the electric power grid, telecommunications, oil and gas pipelines, and transportation networks. This paper will focus on telecommunication networks and the spatial implications of their susceptibility to targeted attack. Utilizing a database of national data carriers, simulations will be run to determine the repercussions of targeted attacks and what the relative merits of different methods of identifying critical nodes are. The analysis will include comparison of current methods employed in vulnerability analysis with spatially constructed methods incorporating regional and distance variables. In addition to the vulnerability analysis a method will be proposed to analyze the fusion of physical and logical networks, and will discuss what new avenues this approach reveals. The results of the analysis will be placed in the context of national and regional security and economic impact.
[show abstract][hide abstract] ABSTRACT: Cybersecurity is an issue of increasing concern since the events of September 11th. Many questions have been raised concerning the security of the Internet and the rest of the US's information infrastructure. This paper begins to examine the issue by analyzing the Internet's autonomous system (AS) map. Using the AS map, malicious infections are simulated and different defense strategies are considered in a cost benefit framework. The results show that protecting the most connected nodes provides significant gains in security and that after the small minority of most connected nodes are protected there are diminishing returns for further protection. Although if parts of the small minority are not protected, such as non-US networks, protection levels are significantly decreased.
[show abstract][hide abstract] ABSTRACT: Exxon Mobil and ConocoPhillips stock price has been predicted using the difference between core and headline CPI in the United States. Linear trends in the CPI difference allow accurate prediction of the prices at a five to ten-year horizon.
European Regional Science Association, ERSA conference papers. 01/2003;
[show abstract][hide abstract] ABSTRACT: Improvements in telecommunications and transportation appear to be bringing the world closer making physical location less of a factor in determining interaction between nations. The formation of regional and global trading pacts and arrangements seem to be further contribution to this interaction. Some would argue that what is evolving, as a result of these developments, is a 'small world' network. This type of network has a high degree of cliquishness, or local connectivity, and a relatively short average minimum path, or strong overall network connectivity. 'Small-world networks' is a new concept that is receiving a lot of attention. Introduced by Watts and Strogatz (1998), a 'small-world network' is based on 'six degrees of separation' or the notion that everyone in the world is related to everyone else through at most six acquaintances. 'Six degrees of separation' arises from the existence of cliques and a few popular individuals who provide connections between these cliques. The huge appeal of 'small-world networks' lies in the impact they are said to have on dynamical systems. According to Watts and Strogatz(1998), for example, models of dynamical systems with small-world coupling display enhanced signal propagation speed, computational power, and synchronizability. Furthermore, contagious diseases tend to spread more freely in 'small-world networks'. These findings have profound implications for many manmade and natural systems. In a trading network, 'small-world' topology might contribute to the regional and global economic spillover effects. This paper introduces a method, based on shift-share analysis and one-way analysis of variance (ANOVA), which can be used to measure the extent of 'small-world' connectivity is evolving in a network. The shift-share model is basically a rule of thumb/empirical method and is used in identifying the "small world" activity. ANOVA is used as a theoretical explanation of the shift-share results and an alternate way to measure "small world". The model is applied to two distinct time periods, the first from 1996 to 1998 and the second from 1989 to 1992. The first time period is representative of the trading network topology that was present in the 1980's, in particular a lot of local trading arrangements (cliques) and very few multilateral alliances and agreements between nations of different cliques, while the latter time period reflects stronger local trading arrangements (cliques) and the introduction of multilateral and bilateral agreements between nations of different cliques. Results are summarized using a geographic information system.