TY - JOUR
T1 - Reprint of
T2 - Using Trellis software to enhance high-quality large-scale network data collection in the field
AU - Lungeanu, Alina
AU - McKnight, Mark
AU - Negron, Rennie
AU - Munar, Wolfgang
AU - Christakis, Nicholas A.
AU - Contractor, Noshir S.
N1 - Funding Information:
This research was supported by the Bill & Melinda Gates Foundation through grants [ OPP1135005 ] to George Washington University and [ OPP1098684 ] to Yale University, the Robert Wood Johnson Foundation , grant number [ 71217 ], and the National Institutes of Health, grant [ P30-AG034420 ] from the National Institute on Aging.
Publisher Copyright:
© 2022 The Authors
PY - 2022/5
Y1 - 2022/5
N2 - 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.
AB - 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.
KW - Graphical interface
KW - Mobile social network survey technologies
KW - Online surveys
KW - Rural network data collection
KW - Software data collection
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U2 - 10.1016/j.socnet.2022.01.004
DO - 10.1016/j.socnet.2022.01.004
M3 - Article
AN - SCOPUS:85123734672
SN - 0378-8733
VL - 69
SP - 293
EP - 306
JO - Social Networks
JF - Social Networks
ER -