Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4937835 | Computers in Human Behavior | 2016 | 6 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Chad Edwards, Austin J. Beattie, Autumn Edwards, Patric R. Spence,