Social network analysis-based conflict relationship investigation and conflict degree-based consensus reaching process for large scale decision making using sparse representation

2019 ◽  
Vol 50 ◽  
pp. 251-272 ◽  
Author(s):  
Ru-Xi Ding ◽  
Xueqing Wang ◽  
Kun Shang ◽  
Francisco Herrera
Author(s):  
Wendong Wu ◽  
Fang He ◽  
Taozhi Zhuang ◽  
Yuan Yi

Currently, many large Chinese cities have entered the postindustrial era, leaving a large amount of vacant, inefficiently utilized industrial land and buildings in the inner cities. Industrial land redevelopment (ILR) can benefit cities in multiple ways, such as by increasing urban public space, improving the quality of life of citizens, and improving the environment, and is considered an effective approach to enhance people’s wellbeing. However, large-scale ILR projects often raise a series of social issues in practice, such as injustice and inequality. To address complex urban issues, ILR requires multifaceted, coordinated, and comprehensive strategies involving multitudinous stakeholders. A profound understanding of diverse stakeholders in the decision-making of ILR is a vital step in enhancing the sustainability of ILR. The aim of this paper is to use Shanghai as a case study to understand the diverse stakeholders and their participation during the decision-making of ILR in China. Interviews and questionnaires were used to collect data. Stakeholder analysis (SA) and social network analysis (SNA) were used as complementary research methodologies in this paper. First, stakeholders who participated in the decision-making of ILR were identified. Then, the characteristics of various stakeholders, including power, interests, and knowledge, were analyzed. Following this, the interactive relationships among stakeholders were explored, and their network structure was examined. Finally, policy recommendations were presented regarding stakeholder participation problems in the decision-making of ILR in China.


PLoS ONE ◽  
2016 ◽  
Vol 11 (1) ◽  
pp. e0146220 ◽  
Author(s):  
Aleksandra do Socorro da Silva ◽  
Silvana Rossy de Brito ◽  
Nandamudi Lankalapalli Vijaykumar ◽  
Cláudio Alex Jorge da Rocha ◽  
Maurílio de Abreu Monteiro ◽  
...  

2013 ◽  
Vol 28 (3) ◽  
pp. 577-587 ◽  
Author(s):  
Donghyun Kim ◽  
Deying Li ◽  
Omid Asgari ◽  
Yingshu Li ◽  
Alade O. Tokuta ◽  
...  

2017 ◽  
Vol 43 (11) ◽  
pp. 1566-1581 ◽  
Author(s):  
Ralf Wölfer ◽  
Eva Jaspers ◽  
Danielle Blaylock ◽  
Clarissa Wigoder ◽  
Joanne Hughes ◽  
...  

Traditionally, studies of intergroup contact have primarily relied on self-reports, which constitute a valid method for studying intergroup contact, but has limitations, especially if researchers are interested in negative or extended contact. In three studies, we apply social network analyses to generate alternative contact parameters. Studies 1 and 2 examine self-reported and network-based parameters of positive and negative contact using cross-sectional datasets ( N = 291, N = 258), indicating that both methods help explain intergroup relations. Study 3 examines positive and negative direct and extended contact using the previously validated network-based contact parameters in a large-scale, international, and longitudinal dataset ( N = 12,988), demonstrating that positive and negative direct and extended contact all uniquely predict intergroup relations (i.e., intergroup attitudes and future outgroup contact). Findings highlight the value of social network analysis for examining the full complexity of contact including positive and negative forms of direct and extended contact.


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