Undermining and Strengthening Social Networks through Network Modification

Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention

Identification and Description of Potentially Influential Social Network Members using the Strategic Player Approach

Background: Diffusion of innovations theory posits that ideas and behaviors can be spread through social network ties. In intervention work, intervening upon certain network members may lead to intervention effects “diffusing” into the network to affect the behavior of network members who did not receive the intervention. The strategic players (SP) method, an extension of Borgatti’s Key Players approach, is used to balance the (sometimes) opposing goals of spreading the intervention to as many members of the target group as possible, while preventing the spread of the intervention to others. Objectives: We sought to test whether members of the SP set have network position and non-network differences (such as demographic, attitudinal, or behavioral differences) compared to the remaining members of the target group (non-SPs). Methods: A first-year class at a private residential university (N = 1342) completed network and non-network measures. Analyses were restricted only to heavy drinkers, leading to a final analytic sample of 529. Results: SPs and non-SPs differed on multiple network variables, but did not differ on most demographic, attitudinal, and behavior variables. Conclusions: As designed, the SP program identified participants who were distinguished by their network position. The fact that they did not also differ on other characteristics shows the SPs are not significantly different than heavy drinkers who were not selected

Systematic comparison of trip distribution laws and models

Trip distribution laws are basic for the travel demand characterization needed in transport and urban planning. Several approaches have been considered in the last years. One of them is the so-called gravity law, in which the number of trips is assumed to be related to the population at origin and destination and to decrease with the distance. The mathematical expression of this law resembles Newton's law of gravity, which explains its name. Another popular approach is inspired by the theory of intervening opportunities which argues that the distance has no effect on the destination choice, playing only the role of a surrogate for the number of intervening opportunities between them. In this paper, we perform a thorough comparison between these two approaches in their ability at estimating commuting flows by testing them against empirical trip data at different scales and coming from different countries. Different versions of the gravity and the intervening opportunities laws, including the recently proposed radiation law, are used to estimate the probability that an individual has to commute from one unit to another, called trip distribution law. Based on these probability distribution laws, the commuting networks are simulated with different trip distribution models. We show that the gravity law performs better than the intervening opportunities laws to estimate the commuting flows, to preserve the structure of the network and to fit the commuting distance distribution although it fails at predicting commuting flows at large distances. Finally, we show that the different approaches can be used in the absence of detailed data for calibration since their only parameter depends only on the scale of the geographic unit.Comment: 15 pages, 10 figure

Great cities look small

Great cities connect people; failed cities isolate people. Despite the fundamental importance of physical, face-to-face social-ties in the functioning of cities, these connectivity networks are not explicitly observed in their entirety. Attempts at estimating them often rely on unrealistic over-simplifications such as the assumption of spatial homogeneity. Here we propose a mathematical model of human interactions in terms of a local strategy of maximising the number of beneficial connections attainable under the constraint of limited individual travelling-time budgets. By incorporating census and openly-available online multi-modal transport data, we are able to characterise the connectivity of geometrically and topologically complex cities. Beyond providing a candidate measure of greatness, this model allows one to quantify and assess the impact of transport developments, population growth, and other infrastructure and demographic changes on a city. Supported by validations of GDP and HIV infection rates across United States metropolitan areas, we illustrate the effect of changes in local and city-wide connectivities by considering the economic impact of two contemporary inter- and intra-city transport developments in the United Kingdom: High Speed Rail 2 and London Crossrail. This derivation of the model suggests that the scaling of different urban indicators with population size has an explicitly mechanistic origin.Comment: 19 pages, 8 figure

Clustering and networking among small independent hotels: developments over ten years

This paper reports on networking activities amongst a cluster of independent hotels with a view to analysing key variables in network development for SMEs. A comparative, longitudinal element is introduced by reference to an earlier study of the same phenomenon, ten years earlier. Of particular interest is the influence of various forms of social capital in the development of informal networks and the inter-play between co-operation and competition over time. Given the time gap between the two studies, the effect of sectoral changes on network development is also examined. The research revisits and extends a previous study of many of the same hotels which were investigated in 1995 over their formal and informal links that were found to be influenced by such factors across two classifications - the business as unit (proximity, perceptions of quality) and the individual respondent (personal social networks and ethnicity). Extending that analysis, social capital concepts and relevant references to embedded networks and kinship groups and co-operative game rules will be introduced in this paper. A highly concentrated population of small, independent hotels in Central London had been identified in the previous research project and it is from this sample that the current research drew and extended its own sample of hotels. With such a high number of hotels in the area a mixture of ‘snowball’ sampling and self-selection was successfully employed. Of the original 29 hotels, 22 have been re-interviewed and complemented by another 19. Of the remainder of the original sample, several had subsequently merged or failed to survive the intervening period. Face-to-face interviews were conducted with owner-managers in all cases using a structured questionnaire that replicated as much as possible of the original questionnaire, with both open and closed questions to allow some individual expression on relevant topics. The quantitative data obtained will be analysed using UCINET software to generate visual representations of networks alongside statistical and cluster analyses. Both academic and policy implications are likely to arise from this research, such as novel insights from such an unique periodic comparison of networks development, the influence of social capital on (formal and informal) network activities and the changing influence and consolidation of hotel groups through mergers and franchising

Rural Community Participation, Social Networks, and Broadband Use: Examples from Localized and National Survey Data

Although attention has been given to how broadband access is related to economic development in rural areas, scant consideration has been given to how it may be associated with voluntary participation. This issue is important in that numerous studies have shown how much more vital community participation is in rural areas as compared to suburban and urban places. Drawing on three diverse data sets, we examine the influence of broadband access on community participation. In addition, we explore whether broadband access exerts its influence through, in conjunction with, or independent of social networks. The results suggest that broadband access and social network size have independent effects on volunteering in rural places.rural sociology, social networks, broadband, digital inequality, volunteerism, Community/Rural/Urban Development, Research and Development/Tech Change/Emerging Technologies,

Entrepreneurial orientation and performance of SMES in Nigeria. The roles of managerial experience and network ties.

Researchers have argued that the results of the EO-performance relationship are context specific and not universal. They emphasize that the results are mixed and require further investigations to get context specific results in different economies to clarify and address inconclusive arguments. Again, the performance implication of EO is shown to be contingent on several factors, such as the firm network ties and manager’s characteristics, especially in developing countries. It would therefore be very necessary to ascertain the intervening factors influencing the EO-performance relationship in the Nigerian context. Drawing from the resource-based view (RBV) and the resource dependency theory, this research project investigated the moderating and mediating roles of managerial experiences and network ties on the relationship between EO and firm performance. The study applied the structural equation modelling techniques to analyse survey data from Nigeria between 2019-2020 and found that the performance effect of innovativeness and proactiveness is positively significant, while that of risk-taking is insignificant after introducing control variables, such as firm age, firm size, and the industry effect. This study further shows a positive mediating effect of business network ties on the relationship between entrepreneurial orientation (EO) and firm performance. However, the study found that political network ties do not mediate the EO-performance relationship. These findings give unique insight and useful knowledge on how business network ties create optimum benefits in enhancing firm performance in the Nigerian context. Again, this study advances empirical knowledge in the Nigerian context by confirming that managerial experience negatively influences the relationship between innovativeness and firm performance. Finally, the current study expands the EO literature by providing empirical evidence supporting the general assumption that EO positively relates to firm performance and that this finding is consistent across groups (e.g., gender and ownership status). This project contributes empirically to the extant literature in different ways, especially the unique insights and novelty of its findings in Nigeria