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Using Trellis software to enhance high-quality large-scale network data collection in the field.
Lungeanu, Alina; McKnight, Mark; Negron, Rennie; Munar, Wolfgang; Christakis, Nicholas A; Contractor, Noshir S.
Afiliación
  • Lungeanu A; Northwestern University, 2240 Campus Drive, Evanston, IL 60208, United States.
  • McKnight M; Yale University, 17 Hillhouse Avenue, New Haven, CT 06511, United States.
  • Negron R; Yale University, 17 Hillhouse Avenue, New Haven, CT 06511, United States.
  • Munar W; George Washington University, 950 New Hampshire Ave, Washington, DC, 20052, United States.
  • Christakis NA; Yale University, 17 Hillhouse Avenue, New Haven, CT 06511, United States.
  • Contractor NS; Northwestern University, 2240 Campus Drive, Evanston, IL 60208, United States.
Soc Networks ; 66: 171-184, 2021 Jul.
Article en En | MEDLINE | ID: mdl-34219904
ABSTRACT
Trellis is a mobile platform created by the Human Nature Lab at the Yale Institute for Network Science to collect high-quality, location-aware, off-line/online, multi-lingual, multi-relational social network and behavior data in hard-to-reach communities. Respondents use Trellis to identify their social contacts by name and photograph, a procedure especially useful in low-literacy populations or in contexts where names may be similar or confusing. We use social network data collected from 1,969 adult respondents in two villages in Kenya to demonstrate Trellis' ability to provide unprecedented metadata to monitor and report on the data collection process including artifactual variability based on surveyors, time of day, or location.
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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Soc Networks Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Soc Networks Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos