Animating the development of Social Networks over time using a dynamic extension of multidimensional scaling

The animation of network visualizations poses technical and theoretical challenges. Rather stable patterns are required before the mental map enables a user to make inferences over time. In order to enhance stability, we developed an extension of stress-minimization with developments over time. This dynamic layouter is no longer based on linear interpolation between independent static visualizations, but change over time is used as a parameter in the optimization. Because of our focus on structural change versus stability the attention is shifted from the relational graph to the latent eigenvectors of matrices. The approach is illustrated with animations for the journal citation environments of Social Networks, the (co-)author networks in the carrying community of this journal, and the topical development using relations among its title words. Our results are also compared with animations based on PajekToSVGAnim and SoNIA

Partnership Development Among Mental Health Organizations

Mental health organizations can play a key role in enhancing youths\u27 access to care by working together to bridge gaps in service delivery systems. This dissertation study examines partnerships among a network of children\u27s behavioral health organizations. The specific aims are to (1) describe and understand the network of partnerships among members of the Children\u27s Services Coalition, (2) assess the capacity of the system to provide coordinated service delivery, and (3) test how patterns of organizational characteristics influence conditions that facilitate and inhibit partnerships among the Children\u27s Service Coalition organizations. This dissertation is a predominantly quantitative cross-sectional network study of 36 children\u27s mental health organizations in St. Louis County that are members of the newly formed Children\u27s Services Coalition. Network data on relationships and archival data from IRS 990 forms were collected and used to explain how organizational characteristics might lead certain organizations to partner, but create conditions that simultaneously facilitate and hinder the degree to which organizations partner. Overall, the key findings describe partnership behavior at the network, small-group, and dyadic-level. First, children\u27s behavioral health organizations in the CSC maintain a complex set of partnerships, which are expected to grow as new opportunities emerge. Second, although partnerships are very common, the larger network may not be well coordinated as evidenced by the few systematic partnership patterns uncovered using descriptive network analysis techniques including sub-group analysis and blockmodeling. However there is potential for coordination at the sub-group level among small groups of similar organizations. Finally, at the dyadic-level, results of a path analysis demonstrate how similar competing organizations depend on one another for resources and benefit from their collaboration, which drives partnerships. Results suggest that organizational interests drive partnership development in this network, and bring together competing organizations that provide similar resources potentially as a strategy for managing competition, or creating efficiencies. This trend runs counter to system reform goals for bridging organizations with complementary services to facilitate access to quality care

A LONGITUDINAL STATISTICAL NETWORK ANALYSIS OF THE ENVIRONMENTAL ITIGATION AND ALLIANCES IN THE UNITED STATES, 1970-2001

This dissertation investigates the structural dynamics of the inter-organizational (litigation, alliance) relations in the environmental movement sector (EMS) in the United States, 1970-2001. Particularly, it focuses on the litigative and alliance ties between the environmental organizations (EORGs) including both environmental movement organizations (EMOs) and environmental government agencies (EGAs), and explaining the processes by which the contemporary inter-EORG structure has emerged over time. The methods used in analysis include (balance, structural) partitioning, p-star logit, and categorical data analysis in statistical network analysis. The data analyzed were collected from various sources including LexisNexis and Guide Star and include both organizational attributes and relations. To explicate the dynamic processes by which the contemporary inter-EORG structure has emerged, this dissertation investigates the formation of dyadic, triadic, and network structure with regard to litigative and alliance ties, respectively. Selected fundamental models of network dynamics (transitive dominance, strategic actor, and social balance) help explain the empirical inter-organizational (litigation, alliance) relations in later chapters. The theoretical and empirical findings help better understand the structural and dynamic issues in the study of the environment, social movement, complex organizations, and network evolution

An ontology-based multi-domain model in social network analysis: Experimental validation and case study

Benítez-Andrades, J. A., García-Rodríguez, I., Benavides, C., Alaiz-Moretón, H., & Labra Gayo, J. E. (2020). An ontology-based multi-domain model in social network analysis: Experimental validation and case study. Information Sciences, 540, 390-413. https://doi.org/10.1016/j.ins.2020.06.008[EN] The use of social network theory and methods of analysis have been applied to different domains in recent years, including public health. The complete procedure for carrying out a social network analysis (SNA) is a time-consuming task that entails a series of steps in which the expert in social network analysis could make mistakes. This research presents a multi-domain knowledge model capable of automatically gathering data and carrying out different social network analyses in different domains, without errors and obtaining the same conclusions that an expert in SNA would obtain. The model is represented in an ontology called OntoSNAQA, which is made up of classes, properties and rules representing the domains of People, Questionnaires and Social Network Analysis. Besides the ontology itself, different rules are represented by SWRL and SPARQL queries. A Knowledge Based System was created using OntoSNAQA and applied to a real case study in order to show the advantages of the approach. Finally, the results of an SNA analysis obtained through the model were compared to those obtained from some of the most widely used SNA applications: UCINET, Pajek, Cytoscape and Gephi, to test and confirm the validity of the model.SIJunta de Castilla y Leó

An Ontology-Based multi-domain model in Social Network Analysis: Experimental validation and case study

The use of social network theory and methods of analysis have been applied to different domains in recent years, including public health. The complete procedure for carrying out a social network analysis (SNA) is a time-consuming task that entails a series of steps in which the expert in social network analysis could make mistakes. This research presents a multi-domain knowledge model capable of automatically gathering data and carrying out different social network analyses in different domains, without errors and obtaining the same conclusions that an expert in SNA would obtain. The model is represented in an ontology called OntoSNAQA, which is made up of classes, properties and rules representing the domains of People, Questionnaires and Social Network Analysis. Besides the ontology itself, different rules are represented by SWRL and SPARQL queries. A Knowledge Based System was created using OntoSNAQA and applied to a real case study in order to show the advantages of the approach. Finally, the results of an SNA analysis obtained through the model were compared to those obtained from some of the most widely used SNA applications: UCINET, Pajek, Cytoscape and Gephi, to test and confirm the validity of the model

A Web-Based Tool for Automatic Data Collection, Curation, and Visualization of Complex Healthcare Survey Studies including Social Network Analysis

There is a great concern nowadays regarding alcohol consumption and drug abuse, especially in young people. Analyzing the social environment where these adolescents are immersed, as well as a series of measures determining the alcohol abuse risk or personal situation and perception using a number of questionnaires like AUDIT, FAS, KIDSCREEN, and others, it is possible to gain insight into the current situation of a given individual regarding his/her consumption behavior. But this analysis, in order to be achieved, requires the use of tools that can ease the process of questionnaire creation, data gathering, curation and representation, and later analysis and visualization to the user. This research presents the design and construction of a web-based platform able to facilitate each of the mentioned processes by integrating the different phases into an intuitive system with a graphical user interface that hides the complexity underlying each of the questionnaires and techniques used and presenting the results in a flexible and visual way, avoiding any manual handling of data during the process. Advantages of this approach are shown and compared to the previous situation where some of the tasks were accomplished by time consuming and error prone manipulations of data