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

Alina Lungeanu¹, Mark McKnight², Rennie Negron²

¹Northwestern University, 2240 Campus Drive, Evanston, IL 60208, United States.

Social Networks

|July 5, 2021

Summary

Trellis is a mobile platform for collecting social network data in remote areas. It provides detailed metadata to monitor data collection quality and identify potential biases.

Keywords:

Graphical interface Mobile social network survey technologies Online surveys Rural network data collection Software data collection

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Area of Science:

Social Network Analysis
Mobile Data Collection
Public Health Research

Background:

Collecting social network data in hard-to-reach communities presents significant challenges.
Traditional methods often struggle with literacy, language barriers, and data accuracy.

Purpose of the Study:

To introduce and evaluate Trellis, a mobile platform for robust social network data collection.
To demonstrate Trellis's capability in generating metadata for process monitoring.

Main Methods:

Utilized the Trellis mobile platform for data collection in two Kenyan villages.
Collected data from 1,969 adult respondents, including social contacts identified by name and photograph.
Leveraged Trellis's location-aware and offline/online capabilities.

Main Results:

Trellis successfully collected high-quality, multi-relational social network and behavioral data.
The platform provided unprecedented metadata on the data collection process.
Identified artifactual variability related to surveyors, time of day, and location.

Conclusions:

Trellis is an effective tool for gathering social network data in challenging environments.
The metadata generated by Trellis enhances transparency and quality control in research.
The platform has significant implications for understanding behavior in underserved populations.