A sustainable tourism development in Alacati, Turkey : (Re)invention of public space with clean energy

Although there is an increasing recognition of the impacts of climate change on communities, residents often resist changing their lifestyle to reduce the effects of the problem. By using a landscape architectural design medium, this paper argues that public space, when designed as an ecological system, has the capacity to create social and environmental change and to increase the quality of the human environment. At the same time, this ecological system can engage residents, enrich the local economy, and increase the social network. Through methods of design, research and case study analysis, an alternative master plan is proposed for a sustainable tourism development in Alacati, Turkey. Our master plan uses local geographical, economic and social information within a sustainable landscape architectural design scheme that addresses the key issues of ecology, employment, public space and community cohesion. A preliminary community empowerment model (CEM) is proposed to manage the designs. The designs address: the coexistence of local agricultural and sustainable energy generation; state of the art water management; and the functional and sustainable social and economic interrelationship of inhabitants, NGOs, and local government

Investigación cualitativa. Comprender al usuario de la información

Content analysis, grounded theory, discourse analysis and social network analysis are analyzed in the context of research on how users generate and share information in everyday life and in the context of social media. For each of the three designs, the research ques on, methods of data analysis and research output are studied. This combina on of three methodologies is valuable to gain knowledge about the user in that environment, de ning the object of study from various aspects of user interation with information

Pediatric pain and anxiety: A meta-analysis of outcomes for a behavioral telehealth intervention

The utility of using single system designs in an optimal set of circumstances is considered. The effects of a computer network intervention on three outcomes (pain intensity, pain aversiveness and anxiety) were explored in previous evaluations via restricted alternating treatment designs. This paper presents an overview of the results of those evaluations, along with new metaanalyses that combine results across all three studies and explore potential moderating variables. This is followed by a discussion of the utility of this approach for social work research. Final version of the manuscript for citation: Holden, G., Bearison, D., Rode, D., Fishman-Kapiloff, M., Rosenberg, G. & Onghena, P. (2003). Pediatric pain and anxiety: A meta-analysis of outcomes for a behavioral telehealth intervention. Research on Social Work Practice, 13, 693-704

Statistical Designs for Network A/B Testing

A/B testing refers to the statistical procedure of experimental design and analysis to compare two treatments, A and B, applied to different testing subjects. It is widely used by technology companies such as Facebook, LinkedIn, and Netflix, to compare different algorithms, web-designs, and other online products and services. The subjects participating in these online A/B testing experiments are users who are connected in different scales of social networks. Two connected subjects are similar in terms of their social behaviors, education and financial background, and other demographic aspects. Hence, it is only natural to assume that their reactions to online products and services are related to their network adjacency. In this research, we propose to use the conditional autoregressive model (CAR) to present the network structure and include the network effects in the estimation and inference of the treatment effect. The following statistical designs are presented: D-optimal design for network A/B testing, a re-randomization experimental design approach for network A/B testing and covariate-assisted Bayesian sequential design for network A/B testing. The effectiveness of the proposed methods are shown through numerical results with synthetic networks and real social networks

Advances to network analysis theories and methods with applications in social, organizational, and crisis settings

This dissertation proposes several solutions to the advancement of network analysis theories and methods with specific applications in the domains of social, organizational, and crisis scenarios. The field of network analysis has attracted interest from scholars coming from a wide range of disciplines as it provides valuable theoretical and methodological toolkits to investigate complex systems of social relations. Furthermore, network theories and methods can examine dynamics present at multiple levels of analysis, from individual- to global-levels. As a result, network analysis has been applied to various contexts of social science research such as social interactions, organizational communication, and crisis response collaboration. In this thesis, I present substantive insights into the application of several network analysis theories and applications to the (1) social, (2) organizational, and (3) crisis response settings. For the context of social interactions, I expand structural balance evaluation to signed and directed networks, and apply this approach to examine 12 social networks. For the context of organizational communication, I demonstrate the application of multilevel modeling for egocentric networks to examine factors associated with the formation of interdisciplinary ties in a scientific organization. In addition, I leverage an extended version of structural balance evaluation for signed and directed networks to examine the sources of tension present in three organizational networks. Third, I provide a case study of response dynamics during the 2010 Haiti earthquake by examining collaboration networks prescribed by national guidelines for response, and interaction networks of the actual collaborations that took place during the earthquake response. Altogether, this work contributes to the growing literature on the theories and applications of network analysis to real-world social networks. In particular, the study designs and findings developed in this thesis can provide a framework for network-based studies from many domains of interest, that includes components of network theories and methods that can help explain the social mechanisms involved in tie formation

Use of social network analysis methods to study professional advice and performance among healthcare providers: a systematic review.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015019328

A holistic framework for environmental change: socio-environmental cohesion for sustainability

Research purpose: Environmental issues have become a regular debate within social, business and political arenas. The need to combine social, environmental and economic systems to achieve a sustainable future (Triple Bottom Line), is gaining prominence within many international development projects. The study of traditional business Environmental Management Systems (EMS) leads to the observation that such systems place primary emphasis upon economic and environmental factors. The project begins with the proposal that an EMS built by an organisations employees' has a greater potential to identify practical environmental impacts and reduce social resistance to change.Methods: This thesis details the development of a seven-stage framework for environmental change referred to as Socio-Environmental Cohesion for Sustainability (SECS). The framework is trialled within a case study organisation (OrgX) using an interpretivist philosophy of social constructionism to guide the research. An action research project is conducted with the researcher acting as an observing participant of the change process. The developed framework follows a multimethodology design of organisational engagement, with strong emphasis placed upon the social values that can drive environmental management practices. The combination of cybernetic and social tools of organisational analysis is shown to provide a unique approach to environmental strategy design; Viable Systems Model, Team Syntegrity, Cultural Analysis, Social Network Analysis.Results: The Cultural and Social Network Analyses provide evidence of an informal environmental network (EWG) contained within OrgX, and identify the core social environmental values of the employee group. A Team Syntegrity workshop is performed and develops a bottom-up participatory approach to environmental strategy designs between the EWG and business management. Following the workshop, OrgX is shown to implement 56% of the developed environmental strategy within eight months. The Viable Systems Model is used to diagnose the organisations structure, which is then combined with the Social Network Analysis to establish the outreach of the EWG.Conclusions: The recognition of the informal environmental network as an official management committee, improvements to operational efficiency and practical benefits to onsite biodiversity, indicates that the SECS framework is capable of addressing all aspects of the Triple Bottom Line

Investigación cualitativa. Comprender al usuario de la información

Content analysis, grounded theory, discourse analysis and social network analysis are analyzed in the context of research on how users generate and share information in everyday life and in the context of social media. For each of the three designs, the research ques on, methods of data analysis and research output are studied. This combina on of three methodologies is valuable to gain knowledge about the user in that environment, de ning the object of study from various aspects of user interation with information

Blockchain Network Analysis: A Comparative Study of Decentralized Banks

Decentralized finance (DeFi) is known for its unique mechanism design, which applies smart contracts to facilitate peer-to-peer transactions. The decentralized bank is a typical DeFi application. Ideally, a decentralized bank should be decentralized in the transaction. However, many recent studies have found that decentralized banks have not achieved a significant degree of decentralization. This research conducts a comparative study among mainstream decentralized banks. We apply core-periphery network features analysis using the transaction data from four decentralized banks, Liquity, Aave, MakerDao, and Compound. We extract six features and compare the banks' levels of decentralization cross-sectionally. According to the analysis results, we find that: 1) MakerDao and Compound are more decentralized in the transactions than Aave and Liquity. 2) Although decentralized banking transactions are supposed to be decentralized, the data show that four banks have primary external transaction core addresses such as Huobi, Coinbase, Binance, etc. We also discuss four design features that might affect network decentralization. Our research contributes to the literature at the interface of decentralized finance, financial technology (Fintech), and social network analysis and inspires future protocol designs to live up to the promise of decentralized finance for a truly peer-to-peer transaction network