A protocol for analyzing repeated measures of online group behavior

Area of Science:

• Behavioral Science
• Data Analysis Methodologies
• Computational Social Science

Background:

• Analyzing repeated measures of online group behavior presents challenges due to complex data structures.
• Existing methods may not adequately account for nested hierarchies (weeks within persons, persons within weeks) and temporal dynamics.
• Understanding temporal patterns in online group interactions is crucial for various fields.

Purpose of the Study:

• To introduce a novel, generalizable five-step protocol for analyzing repeated measures of online group behavior.
• To address the complexities of nested data structures and temporal variations in weekly online group activities.
• To provide a replicable framework for researchers using R.

Main Methods:

• A five-step Courtney-Fanguy-Costley protocol is proposed.
• The protocol systematically addresses data structure, defines data levels, and considers variable variation, timing, and aggregation.
• It incorporates methods to ensure necessary variation and specifies null and mixed-effects models.

Main Results:

• The protocol effectively manages and analyzes complex nested data structures common in online group behavior studies.
• It accounts for the temporal nature of behavior across early, mid, and late periods within each week.
• Exemplary R code is provided for practical implementation and replication.

Conclusions:

• The Courtney-Fanguy-Costley protocol offers a robust framework for the analysis of repeated measures in online group behavior.
• This method enhances the understanding of temporal dynamics and nested data in digital interaction research.
• The provided R code facilitates widespread adoption and application of the protocol.