Project Description

Trolling politicians is widespread on social media platforms. These less socially desired behaviors have been associated with the toxic online disinhibition effect, enabled by online anonymity, invisibility, asynchronicity, and minimization of authority, for example. As technological affordances on social media platforms change over time, norms of behaviors do too; the enabling factors of trolling may change from one election cycle to another leading to possible variations in online trolling of politicians. This project will focus on political trolling, using Twitter data from two election cycles, to compare the extent and type of trolling behaviors.

Technology or Computational Component

Students will be scraping data from social media platforms, cleaning the data, and analyzing the data. In addition, training in Nvivo, software for qualitative data analysis, will be provided.