Multi-mode design for studying cyber aggression in texts, Facebook and Twitter messages among middle school youth.

Abstract

With the explosion of the internet, cyber aggression has become one of the fastest growing forms of interpersonal violence. Methods used to understand aggressive communications content have been limited primarily to surveys. Here, we present multiple methods - panel surveys, electronic capture of social media, and Ecological Momentary Assessments - to characterize both behavioral and perceptual components of cyber aggression in a study of youth from two Iowa middle schools during the 2014-2015 school year. Youth completed a survey, and a sub-sample of smartphone owners installed an electronic application that collected over 150,000 text messages, Twitter posts, and Facebook posts. The sub-sample also participated in ecological momentary assessments to collect self-reported experiences of cyber aggression. To code for aggressive content in this large sample of messages, a case-control sampling strategy was used to identify a series of "case" messages from youth who reported aggression and "control" messages from youth who reported no aggression. We further present recruitment protocols, data management and qualitative coding methods as well as descriptive characteristics of the student cohort and nested sample of messages. These methods have potential use in future studies of "big data" captured from social media.