© 2021 IGI Global. All rights reserved. Although algorithms have been widely used to deliver useful services, how users actually experience algorithm-driven news remains unclear. This study examines user attitude and perception of algorithmic journalism and identifies the similarities and differences in experience and satisfaction formation. A comparative study between the United States (U.S.) and South Korea was conducted to examine how the two countries’ users experience the quality of algorithm-driven news services and how individuals perceive the topics of fairness, accountability, and transparency. The notable similarities and differences are found by performing a comparison of cognitive processes. The major attitudes toward algorithm news are similar between the two countries, although the weights placed on the qualities differ. South Korean users put more weight on performance qualities, and U.S. users place relatively greater emphasis on procedural features. Different patterns of algorithm news experience imply the contextual nature of algorithm: how users perceive and feel about topics in algorithm news and how they use and engage with algorithm news depend on the context where the experience is taking place. The analysis suggests the importance of user-perceived issues and the contextual nature of such issues.