The Effects of Anthropomorphism on How People Evaluate Algorithm-Written News
Document Type
Article
Publication Date
1-1-2023
Abstract
Based on the Modality-Agency-Interactivity-Navigability model and the anthropomorphism theory, this study examines whether embedding human-like characteristics in algorithms increases the persuasiveness of algorithm-written news. This study further investigates how different types of relationships (servant or friend) that human writers form with algorithms determine the persuasiveness of algorithm-generated news. Experiment 1 demonstrated that participants who read the human- and humanized algorithm-written news showed greater emotional involvement in the stories and liked the articles more than those who read the algorithm-written news. The participants also reported that news written by humans, humanized algorithms, and algorithms, had equal news credibility. Experiment 2 further showed that the participants perceived the news as more credible and experienced greater degrees of emotional involvement when human writers formed a partner-to-friend relationship with humanized algorithms while generating news rather than a servant-to-master relationship.
Publication Source (Journal or Book title)
Digital Journalism
First Page
103
Last Page
124
Recommended Citation
Jang, W., Chun, J., Kim, S., & Kang, Y. (2023). The Effects of Anthropomorphism on How People Evaluate Algorithm-Written News. Digital Journalism, 11 (1), 103-124. https://doi.org/10.1080/21670811.2021.1976064