| Abstract: | Social interaction, particularly in older adolescents, increasingly involves computer‐mediated communication. Although studies of public computer‐mediated communication are increasingly common, studies of private text messaging remain rare. As approaches for obtaining such data evolve with technological advances, developmental scientists need designs in which to use such approaches that reduce sampling biases in both participants and text messages. In this study (n = 854; 46% male; 22% African American, 60% European American), we examined selection biases in the participant sample (i.e., factors associated with actual participation), procedural biases in the participant sample (i.e., factors related to failed data capture due to technological or procedural issues), and selection biases in the sample of text messages (i.e., based on self‐reported reasons for texting). Findings from our study suggest that studying human interaction directly through analysis of text message data is not only feasible, but also may be successfully undertaken with minimal biases regarding sample selection and text message selection among those who are engaged in research and engaged in text messaging outside of the study context. However, biases may occur depending on the type of platform (iPhone vs. Android) used by participants for texting. |
