Data collection for social network research

2021 ◽  
Author(s):  
Garry Robins ◽  
David Bright ◽  
Laurin Weissinger ◽  
Pat Stys
Author(s):  
Chiara Pomare ◽  
Janet C. Long ◽  
Kate Churruca ◽  
Louise A. Ellis ◽  
Jeffrey Braithwaite

Author(s):  
jimi adams ◽  
Tatiane Santos ◽  
Venice Ng Williams

This chapter provides an overview of social network data collection strategies. We begin by outlining the primary principles of sampling and measurement design, then describing how those combine into what is labeled the “boundary specification problem” for social network research. We accompany these definitions with examples of how these elements are applied across ego, partial, and complete network designs. Next, the chapter turns to the primary ways that network data have been evaluated, highlighting both the implications of those evaluations for their use in network analyses and various strategies for how the identified limitations can be leveraged for optimal data and analytic quality. The chapter concludes by addressing some of the ethical considerations that are unique to the gathering and analyses of social network data.


2019 ◽  
Author(s):  
jimi adams ◽  
Tatiane Santos ◽  
Venice Ng Williams

This chapter provides an overview of social network data collection strategies. We begin by outlining the primary principles of sampling and measurement design, then describing how those combine into what is labeled as the “boundary specification problem” for social network research. We accompany these definitions with examples of how these elements are applied across ego-, partial- and complete- network designs. Next, the chapter turns to the primary ways that network data have been evaluated, highlighting both the implications of those evaluations for their use in network analyses, and various strategies for how the identified limitations can be leveraged for optimal data and analytic quality. The chapter concludes by addressing some of the ethical considerations that are unique to the gathering and analyses of social network data.


2020 ◽  
Author(s):  
Arunangsu Chatterjee ◽  
Sebastian Stevens ◽  
Sheena Asthana ◽  
Ray B Jones

BACKGROUND Digital health (DH) innovation ecosystems (IE) are key to the development of new e-health products and services. Within an IE, third parties can help promote innovation by acting as knowledge brokers and the conduits for developing inter-organisational and interpersonal relations, particularly for smaller organisations. Kolehmainen’s quadruple helix model suggests who the critical IE actors are, and their roles. Within an affluent and largely urban setting, such ecosystems evolve and thrive organically with minimal intervention due to favourable economic and geographical conditions. Facilitating and sustaining a thriving DH IE within a resource-poor setting can be far more challenging even though far more important for such peripheral economics and the health and well-being of those communities. OBJECTIVE Taking a rural and remote region in the UK, as an instance of an IE in a peripheral economy, we adapt the quadruple helix model of innovation, apply a monitored social networking approach using McKinsey’s Three Horizons of growth to explore: • What patterns of connectivity between stakeholders develop within an emerging digital health IE? • How do networks develop over time in the DH IE? • In what ways could such networks be nurtured in order to build the capacity, capability and sustainability of the DH IE? METHODS Using an exploratory single case study design for a developing digital health IE, this study adopts a longitudinal social network analysis approach, enabling the authors to observe the development of the innovation ecosystem over time and evaluate the impact of targeted networking interventions on connectivity between stakeholders. Data collection was by an online survey and by a novel method, connection cards. RESULTS Self-reported connections between IE organisations increased between the two waves of data collection, with Small and Medium-sized Enterprises (SMEs) and academic institutions the most connected stakeholder groups. Patients involvement improved over time but still remains rather peripheral to the DH IE network. Connection cards as a monitoring tool worked really well during large events but required significant administrative overheads. Monitored networking information categorised using McKinsey’s Three Horizons proved to be an effective way to organise networking interventions ensuring sustained engagement. CONCLUSIONS The study reinforces the difficulty of developing and sustaining a DH IE in a resource-poor setting. It demonstrates the effective monitored networking approach supported by Social Network Analysis allows to map the networks and provide valuable information to plan future networking interventions (e.g. involving patients or service users). McKinsey’s Three Horizons of growth-based categorisation of the networking assets help ensure continued engagement in the DH IE contributing towards its long-term sustainability. Collecting ongoing data using survey or connection card method will become more labour intensive and ubiquitous ethically driven data collection methods can be used in future to make the process more agile and responsive.


2016 ◽  
Vol 79 (3) ◽  
pp. 315-330 ◽  
Author(s):  
Koenraad Brosens ◽  
Klara Alen ◽  
Astrid Slegten ◽  
Fred Truyen

Abstract The essay introduces MapTap, a research project that zooms in on the ever-changing social networks underpinning Flemish tapestry (1620 – 1720). MapTap develops the young and still slightly amorphous field of Formal Art Historical Social Network Research (FAHSNR) and is fueled by Cornelia, a custom-made database. Cornelia’s unique data model allows researchers to organize attribution and relational data from a wide array of sources in such a way that the complex multiplex and multimode networks emerging from the data can be transformed into partial unimode networks that enable proper FAHSNR. A case study revealing the key roles played by women in the tapestry landscape shows how this kind of slow digital art history can further our understanding of early modern creative communities and industries.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chiara Broccatelli ◽  
Peng Wang ◽  
Lisa McDaid ◽  
Mark McCann ◽  
Sharon Anne Simpson ◽  
...  

AbstractThere is growing interest in social network-based programmes to improve health, but rigorous methods using Social Network research to evaluate the process of these interventions is less well developed. Using data from the “STis And Sexual Health” (STASH) feasibility trial of a school-based, peer-led intervention on sexual health prevention, we illustrate how network data analysis results can address key components of process evaluations for complex interventions—implementation, mechanisms of impacts, and context. STASH trained students as Peer Supporters (PS) to diffuse sexual health messages though face-to-face interactions and online Facebook (FB) groups. We applied a Multilevel Exponential Random Graph modelling approach to analyse the interdependence between offline friendship relationships and online FB ties and how these different relationships align. Our results suggest that the creation of online FB communities mirrored offline adolescent groups, demonstrating fidelity of intervention delivery. Data on informal friendship networks related to student’s individual characteristics (i.e., demographics, sexual health knowledge and adherence to norms, which were included for STASH), contributed to an understanding of the social relational ‘building’ mechanisms that sustain tie-formation. This knowledge could assist the selection of opinion leaders, improving identification of influential peers situated in optimal network positions. This work provides a novel contribution to understanding how to integrate network research with the process evaluation of a network intervention.


2021 ◽  
Vol 66 ◽  
pp. 125-138
Author(s):  
Lorien Jasny ◽  
Jesse Sayles ◽  
Matthew Hamilton ◽  
Laura Roldan Gomez ◽  
Derric Jacobs ◽  
...  

2020 ◽  
Vol 6 (2) ◽  
pp. 87-91
Author(s):  
Hartiwi Prabowo ◽  
Rini Kurnia Sari ◽  
Stephanie Bangapadang

The research conducted is to know the impact of social network marketing on consumer purchase intention and consumers who become research are active students at private universities in Jakarta, and how social network marketing also affect consumer engagement (as moderate variable). The research method used in this research is quantitative research method. A method of data collection used in this research is a questionnaire distributed to 119 university students. The results of this study showed that social network marketing has a strong and significant impact oncustomer engagement, customer engagementhas a strong and significant impact on consumer purchase intention, social network marketing has a strong and significant impact consumer purchase intention, and also there is a significant impact from social network marketing on consumer purchase intention through consumer engagement.


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