Keywords
twitterbots; casa; learning; twitter; cognitive elaboration; bot
Abstract
Twitter’s design allows the implementation of automated programs that can submit tweets, interact with others, and generate content based on algorithms. Scholars and end-users alike refer to these programs to as “Twitterbots.” This two-part study explores the differences in perceptions of communication quality between a human agent and a Twitterbot in the areas of cognitive elaboration, information seeking, and learning outcomes. In accordance with the Computers Are Social Actors (CASA) framework (Reeves & Nass, 1996), results suggest that participants learned the same from either a Twitterbot or a human agent. Results are discussed in light of CASA, as well as implications and directions for future studies.
Date Created
January 2016
STARS Citation
Edwards, Chad; Beattie, Austin; Edwards, Autumn; and Spence, Patric, "Differences in perceptions of communication quality between a Twitterbot and human agent for information seeking and learning" (2016). EGS Content. 83.
https://stars.library.ucf.edu/egs_content/83
https://works.bepress.com/patric-spence/24/download/