Social network analysis software

Abstract: The networked governance performance in emergency management is dependent on structural, spatial, and temporal issues embedded into interorganizational relationships. Network sustainability is one of such issues that requires due attention by scholars and practitioners in the field. This article examines how network sustainability, namely, the extent to which network relationships are maintained and nurtured over time, is affected by interdependent network relationships, network complexity, and information-communication technology (ICT) utilization at the local level. Based on 118 responses from a self-administered survey distributed to four county-based metropolitan regions in the state of Florida, this study provides a multiple linear regression analysis. Using UCINET social network analysis software, additional analysis of the network structure and relationships in the four counties is provided for further insight. The findings suggest positive and statistically significant relationships between networ...

Abstract: Social network analysis quantifies and visualizes relationships between and among individuals or organizations. Applications in the health sector remain underutilized. This systematic review seeks to analyze what social network methods have been used to study professional communication and performance among healthcare providers. Ten databases were searched from 1990 through April 2016, yielding 5970 articles screened for inclusion by two independent reviewers who extracted data and critically appraised each study. Inclusion criteria were study of health care worker professional communication, network methods used, and patient outcomes measured. The search identified 10 systematic reviews. The final set of articles had their citations prospectively and retrospectively screened. We used narrative synthesis to summarize the findings. The six articles meeting our inclusion criteria described unique health sectors: one at primary healthcare level and five at tertiary level; five conducted in the USA, one in Australia. Four studies looked at multidisciplinary healthcare workers, while two focused on nurses. Two studies used mixed methods, four quantitative methods only, and one involved an experimental design. Four administered network surveys, one coded observations, and one used an existing survey to extract network data. Density and centrality were the most common network metrics although one study did not calculate any network properties and only visualized the network. Four studies involved tests of significance, and two used modeling methods. Social network analysis software preferences were evenly split between ORA and UCINET. All articles meeting our criteria were published in the past 5 years, suggesting that this remains in clinical care a nascent but emergent research area. There was marked diversity across all six studies in terms of research questions, health sector area, patient outcomes, and network analysis methods. Network methods are underutilized for the purposes of understanding professional communication and performance among healthcare providers. The paucity of articles meeting our search criteria, lack of studies in middle- and low-income contexts, limited number in non-tertiary settings, and few longitudinal, experimental designs, or network interventions present clear research gaps. PROSPERO CRD42015019328

Abstract: This paper reflects on approaches to collaborative knowledge exchange projects between UK universities and the creative economy. It develops a preliminary account of cultural ecology as a systematic approach to producing impact in the creative economy. It argues that such an approach is a powerful way to aggregate micro-businesses and small and medium sized enterprises in a meaningful network of new relationships. The paper uses social network analysis software to begin to visualise the pattern of relationships that constitute the ecosystem. The paper reports on the work of the Research and Enterprise for Arts and Creative Technologies Hub, one of four Knowledge Exchange Hubs for the Creative Economy established by the Arts and Humanities Research Council.

Abstract: With the broad application of electronic communication monitoring tools and data-sharing techniques, the size of networks to be studied by social network analysis (SNA) has grown rapidly However, current SNA techniques are not particularly scalable For example, even centrality, which is one of the most frequently used SNA parameters, cannot be measured by most current SNA software when the network is large This paper presents the design of an effective and scalable anytime anywhere parallel methodology for SNA with large-scale networks emphasizing centrality measurement algorithms The efficiency and effectiveness of the methodology is validated by experiments of centrality analysis for large networks