Differences in perceptions of communication quality between a Twitterbot and human agent for information seeking and learning. (December 2016) - Edwards, Chad; Beattie, Austin J.; Edwards, Autumn; Spence, Patric R.
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. Highlights: Twitterbots were compared to human agents for information seeking and learning. Two experimental studies were conducted. No differences in cognitive elaboration and information seeking. No differences in affective learning and motivation. Twitterbots may be effective agents for communication in social media environments.