696 resultados para Social networks and Religious
Resumo:
The paper presents a critical analysis of the extant literature pertaining to the networking behaviours of young jobseekers in both offline and online environments. A framework derived from information behaviour theory is proposed as a basis for conducting further research in this area. Method. Relevant material for the review was sourced from key research domains such as library and information science, job search research, and organisational research. Analysis. Three key research themes emerged from the analysis of the literature: (1) social networks, and the use of informal channels of information during job search, (2) the role of networking behaviours in job search, and (3) the adoption of social media tools. Tom Wilson’s general model of information behaviour was also identified as a suitable framework to conduct further research. Results. Social networks have a crucial informational utility during the job search process. However, the processes whereby young jobseekers engage in networking behaviours, both offline and online, remain largely unexplored. Conclusion. Identification and analysis of the key research themes reveal opportunities to acquire further knowledge regarding the networking behaviours of young jobseekers. Wilson’s model can be used as a framework to provide a holistic understanding of the networking process, from an information behaviour perspective.
Resumo:
The present investigation aims to analyse the relationship between knowledge sharing behaviours and performance. The former behaviours were studied using Social Network Analysis, in an attempt to characterise knowledge sharing networks. Through identification of central individuals in these networks, we made analysis of the association between this centrality and individual performance. A questionnaire was developed and applied to a sample of workers in a Portuguese organisation (N=244). The final conclusions point to a positive association between these behaviours and individual performance.
Resumo:
In this dissertation, we apply mathematical programming techniques (i.e., integer programming and polyhedral combinatorics) to develop exact approaches for influence maximization on social networks. We study four combinatorial optimization problems that deal with maximizing influence at minimum cost over a social network. To our knowl- edge, all previous work to date involving influence maximization problems has focused on heuristics and approximation. We start with the following viral marketing problem that has attracted a significant amount of interest from the computer science literature. Given a social network, find a target set of customers to seed with a product. Then, a cascade will be caused by these initial adopters and other people start to adopt this product due to the influence they re- ceive from earlier adopters. The idea is to find the minimum cost that results in the entire network adopting the product. We first study a problem called the Weighted Target Set Selection (WTSS) Prob- lem. In the WTSS problem, the diffusion can take place over as many time periods as needed and a free product is given out to the individuals in the target set. Restricting the number of time periods that the diffusion takes place over to be one, we obtain a problem called the Positive Influence Dominating Set (PIDS) problem. Next, incorporating partial incentives, we consider a problem called the Least Cost Influence Problem (LCIP). The fourth problem studied is the One Time Period Least Cost Influence Problem (1TPLCIP) which is identical to the LCIP except that we restrict the number of time periods that the diffusion takes place over to be one. We apply a common research paradigm to each of these four problems. First, we work on special graphs: trees and cycles. Based on the insights we obtain from special graphs, we develop efficient methods for general graphs. On trees, first, we propose a polynomial time algorithm. More importantly, we present a tight and compact extended formulation. We also project the extended formulation onto the space of the natural vari- ables that gives the polytope on trees. Next, building upon the result for trees---we derive the polytope on cycles for the WTSS problem; as well as a polynomial time algorithm on cycles. This leads to our contribution on general graphs. For the WTSS problem and the LCIP, using the observation that the influence propagation network must be a directed acyclic graph (DAG), the strong formulation for trees can be embedded into a formulation on general graphs. We use this to design and implement a branch-and-cut approach for the WTSS problem and the LCIP. In our computational study, we are able to obtain high quality solutions for random graph instances with up to 10,000 nodes and 20,000 edges (40,000 arcs) within a reasonable amount of time.
Resumo:
The use of virtual social networks (VSNs) has been prevalent among consumers worldwide. Numerous studies have investigated various aspects of VSNs. However, these studies have mainly focused on students and young adults as they were early adopters of these innovative networks. A search of the literature revealed there has been a paucity of research on adult consumers’ use of VSNs. This research study addressed this gap in the literature by examining the determinants of engagement in VSNs among adult consumers in Singapore. The objectives of this study are to empirically investigate the determinants of engagement in VSNs and to offer theoretical insights into consumers’ preference and usage of VSNs. This study tapped upon several theories developed in the discipline of technology and innovation adoption. These were Roger’s Diffusion of Innovation, Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), Conceptual Framework of Individual Innovation Adoption by Frambach and Schillewaert (2002), Enhanced Model of Innovation Adoption by Talukder (2011), Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and the Information Systems (IS) Success Model. The proposed research model, named the Media Usage Model (MUM), is a framework rooted in innovation diffusion and IS theories. The MUM distilled the essence of these established models and thus provides an updated, lucid explanation of engagement in VSNs. A cross-sectional, online social survey was conducted to collect quantitative data to examine the validity of the proposed research model. Multivariate data analysis was carried out on a data set comprising 806 usable responses by utilizing SPSS, and for structural equation modeling AMOS and SmartPLS. The results indicate that consumer attitude towards VSNs is significantly and positively influenced by: three individual factors – hedonic motivation, incentives and experience; two system characteristics – system quality and information quality; and one social factor – social bonding. Consumer demographics were found to influence people’s attitudes towards VSNs. In addition, consumer experience and attitude towards VSNs significantly and positively influence their usage of VSNs. The empirical data supported the proposed research model, explaining 80% of variance in attitude towards VSNs and 45% of variance in usage of VSNs. Therefore, the MUM achieves a definite contribution to theoretical knowledge of consumer engagement in VSNs by deepening and broadening our appreciation of the intricacies related to use of VSNs in Singapore. This study’s findings have implications for customer service management, services marketing and consumer behavior. These findings also have strategic implications for maximizing efficient utilization and effective management of VSNs by businesses and operators. The contributions of this research are: firstly, shifting the boundaries of technology or innovation adoption theories from research on employees to consumers as well as the boundaries of Internet usage or adoption research from students to adults, which is also known as empirical generalization; secondly, highlighting the issues associated with lack of significance of social factors in adoption research; and thirdly, augmenting information systems research by integrating important antecedents for success in information systems.
Resumo:
Over the last few years, football entered in a period of accelerated access to large amount of match analysis data. Social networks have been adopted to reveal the structure and organization of the web of interactions, such as the players passing distribution tendencies. In this study we investigated the influence of ball possession characteristics in the competitive success of Spanish La Liga teams. The sample was composed by OPTA passing distribution raw data (n=269,055 passes) obtained from 380 matches involving all the 20 teams of the 2012/2013 season. Then, we generated 760 adjacency matrixes and their corresponding social networks using Node XL software. For each network we calculated three team performance measures to evaluate ball possession tendencies: graph density, average clustering and passing intensity. Three levels of competitive success were determined using two-step cluster analysis based on two input variables: the total points scored by each team and the scored per conceded goals ratio. Our analyses revealed significant differences between competitive performances on all the three team performance measures (p < .001). Bottom-ranked teams had less number of connected players (graph density) and triangulations (average clustering) than intermediate and top-ranked teams. However, all the three clusters diverged in terms of passing intensity, with top-ranked teams having higher number of passes per possession time, than intermediate and bottom-ranked teams. Finally, similarities and dissimilarities in team signatures of play between the 20 teams were displayed using Cohen’s effect size. In sum, findings suggest the competitive performance was influenced by the density and connectivity of the teams, mainly due to the way teams use their possession time to give intensity to their game.
Delegation to workers across countries and industries : social capital and coordination needs matter
Resumo:
The degree of delegating authority to non-managerial and non-supervisory workers substantially varies across countries and industries. By examining worker-level data from 14 countries, I empirically explain this variation by region-specific social capital that proxies workers' degree of self-centeredness and the industry-specific need for coordination. The empirical results of this study confirm the theoretical predictions by Alonso et al. (2008) for the first time: the negative association between coordination needs and decentralization is mitigated in regions with lower self-centeredness of workers. In particular, when self-centeredness of workers (respectively, need for coordination) is very low, the degree of delegation is always high regardless of the level of the need for coordination (self-centeredness of workers). Positive associations between delegation and its benefits, including job satisfaction, wages (proxy for higher productivity), and skill upgrading of workers, are also found. These results imply that people's degree of self-centeredness affects a country's economic development patterns by changing the degree of decentralization and its benefits.
Resumo:
En base a los resultados obtenidos en investigaciones efectuadas por el grupo de investigación del Instituto de Investigaciones en Humanidades y Ciencias Sociales (UNLP-CONICET) sobre redes sociales en distintos tipos de bibliotecas (de investigación, universitarias y populares) en Argentina, se efectúa un balance sobre su uso en este tipo de instituciones y se proponen lineamientos para la formulación de una política comunicacional que las contemple y forme parte del plan de gestión de estas unidades de información. Los mismos apuntan a considerar cabalmente todos los aspectos vinculados a los alcances, limitaciones, usos, riesgos y demás que implica la adopción y la apropiación de diferentes redes sociales (tales como Facebook, Twitter, entre otras), su convivencia, gestión y sustentabilidad a lo largo del tiempo
Resumo:
In this thesis, we investigate the role of applied physics in epidemiological surveillance through the application of mathematical models, network science and machine learning. The spread of a communicable disease depends on many biological, social, and health factors. The large masses of data available make it possible, on the one hand, to monitor the evolution and spread of pathogenic organisms; on the other hand, to study the behavior of people, their opinions and habits. Presented here are three lines of research in which an attempt was made to solve real epidemiological problems through data analysis and the use of statistical and mathematical models. In Chapter 1, we applied language-inspired Deep Learning models to transform influenza protein sequences into vectors encoding their information content. We then attempted to reconstruct the antigenic properties of different viral strains using regression models and to identify the mutations responsible for vaccine escape. In Chapter 2, we constructed a compartmental model to describe the spread of a bacterium within a hospital ward. The model was informed and validated on time series of clinical measurements, and a sensitivity analysis was used to assess the impact of different control measures. Finally (Chapter 3) we reconstructed the network of retweets among COVID-19 themed Twitter users in the early months of the SARS-CoV-2 pandemic. By means of community detection algorithms and centrality measures, we characterized users’ attention shifts in the network, showing that scientific communities, initially the most retweeted, lost influence over time to national political communities. In the Conclusion, we highlighted the importance of the work done in light of the main contemporary challenges for epidemiological surveillance. In particular, we present reflections on the importance of nowcasting and forecasting, the relationship between data and scientific research, and the need to unite the different scales of epidemiological surveillance.
Resumo:
PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.
Resumo:
The objective of this study was to review the Brazilian epidemiologic literature on periodontal outcomes and socio-demographic factors, assessing bibliographic and methodological characteristics of this scientific production, as well as the consistency and statistical significance of the examined associations. A systematic review was carried out in six bibliographic sources. The review was limited to the period between 1999 and 2008, without any other type of restriction. Among the 410 papers identified, 29 were included in the review. An increasing number of articles, specifically in the last four years of study, was observed. However, there is a concentration of studies in the South and Southeast regions of Brazil, and many of them are not closely connected to theoretical formulations in the field. In spite of these shortcomings, the review findings corroborate the idea that poor socioeconomic conditions are associated with periodontal outcomes, as demonstrated primarily by income and schooling indicators.
Remembering sport history: Narrative, social memory and the origins of the rugby league in Australia
Resumo:
This study examines the historiography of the origins of rugby league in Australia. By accepting the inclusive nature of representation of the past as found in social memory theory, a wide range of sources ranging from histories written by academics to annuals, yearbooks and newspaper books are consulted. These sources reveal that there are several competing and conflicting accounts of the emergence of rugby league in Australia. These divergent accounts are used to facilitate a discussion of the role of narrative in sport history This article argues that narrative is an integral, not optional, feature of the production of history and that the historography of the origins of rugby league highlight the problematic nature of objectivity in history and the unavoidable, impositionalist role of the historian.
Resumo:
The clash between German Social Democracy--the party, intellectuals and workers--and the German Imperial State was played out in the Freie Volksbahne (Free People's Theatre) founded by intellectuals to energise working class political awareness of drama with a political and social cutting edge. It fell foul of state censorship, lost its bite, yet prospered.