Using Trellis software to enhance high-quality large-scale network data collection in the field

Alina Lungeanu; Mark McKnight; Rennie Negron; Wolfgang Munar; Nicholas A Christakis; Noshir S Contractor

doi:10.1016/j.socnet.2021.02.007

Using Trellis software to enhance high-quality large-scale network data collection in the field

Soc Networks. 2021 Jul:66:171-184. doi: 10.1016/j.socnet.2021.02.007.

Authors

Alina Lungeanu¹, Mark McKnight², Rennie Negron², Wolfgang Munar³, Nicholas A Christakis², Noshir S Contractor¹

Affiliations

¹ Northwestern University, 2240 Campus Drive, Evanston, IL 60208, United States.
² Yale University, 17 Hillhouse Avenue, New Haven, CT 06511, United States.
³ George Washington University, 950 New Hampshire Ave, Washington, DC, 20052, United States.

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.

Keywords: Graphical interface; Mobile social network survey technologies; Online surveys; Rural network data collection; Software data collection.

Grants and funding

P30 AG034420/AG/NIA NIH HHS/United States