ChatDashboard: A Framework to collect, link, and process donated WhatsApp Chat Log Data.

Area of Science:

• Social Sciences
• Communication Studies
• Digital Humanities

Background:

• Collecting granular communication data is challenging.
• Existing methods for analyzing interpersonal interactions are often limited.
• WhatsApp chat logs offer rich insights into social dynamics.

Purpose of the Study:

• To introduce ChatDashboard, a novel framework for collecting, linking, and processing donated WhatsApp chat log data.
• To enable researchers to gather transparently donated chat data linked to survey responses.
• To facilitate the study of interpersonal interactions and communication patterns.

Main Methods:

• The ChatDashboard framework includes the WhatsR R package for data preprocessing.
• It features a ChatDashboard R Shiny web app for secure data uploading and review.
• DashboardTester automates framework setup verification through participant simulation.

Main Results:

• ChatDashboard provides a comprehensive solution for researchers to establish their own data collection pipelines.
• The framework allows for retrospective collection of highly granular data on communication.
• It enables linking chat data with survey responses for enriched analysis.

Conclusions:

• ChatDashboard empowers researchers to investigate social relationships using donated WhatsApp data without custom tool development.
• The framework promotes transparent data donation from consenting participants.
• Detailed guidelines are provided for implementing data donation pipelines.