Seeing Is Believing: The Role Of Scatterplots In Recommender System Trust And Decision-Making

The accuracy of recommender systems influences their trust and decision-making when using them. Providing additional information, such as visualizations, offers context that would otherwise be lacking. However, the role of visualizations in influencing trust and decisions with recommender systems is under-explored. To bridge this gap, we conducted a two-part human-subject experiment to investigate the impact of scatterplots on recommender system decisions. Our first study focuses on high-level decisions, such as selecting which recommender system to use. The second study focuses on low-level decisions, such as agreeing or disagreeing with a specific recommendation. Our results show scatterplots accompanied by higher levels of accuracy influence decisions and that participants tended to trust the recommendations more when scatterplots were accompanied by descriptive accuracy (e.g., high, medium, or low) instead of numeric accuracy (e.g., 90%). Furthermore, we observed scatterplots often assisted participants in validating their decisions. Based on the results, we believe that scatterplots and visualizations, in general, can aid in making informed decisions, validating decisions, and building trust in recommendation systems.

Bhavana Doppalapudi, Dilshadur Rahman, Seungbae Kim, and Paul Rosen. Seeing Is Believing: The Role Of Scatterplots In Recommender System Trust And Decision-Making. To appear at the International Symposium on Visual Computing, 2024.

@article{doppalapudi2024seeing,
  title = {Seeing is Believing: The Role of Scatterplots in Recommender System Trust and
    Decision-Making},
  author = {Doppalapudi, Bhavana and Rahman, Dilshadur and Kim, Seungbae and Rosen, Paul},
  journal = {To appear at the International Symposium on Visual Computing},
  year = {2024},
  note = {textit{Presented at the International Symposium on Visual Computing 2024.}},
  abstract = {The accuracy of recommender systems influences their trust and
    decision-making when using them. Providing additional information, such as
    visualizations, offers context that would otherwise be lacking. However, the role of
    visualizations in influencing trust and decisions with recommender systems is
    under-explored. To bridge this gap, we conducted a two-part human-subject experiment to
    investigate the impact of scatterplots on recommender system decisions. Our first study
    focuses on high-level decisions, such as selecting which recommender system to use. The
    second study focuses on low-level decisions, such as agreeing or disagreeing with a
    specific recommendation. Our results show scatterplots accompanied by higher levels of
    accuracy influence decisions and that participants tended to trust the recommendations
    more when scatterplots were accompanied by descriptive accuracy (e.g., high, medium, or
    low) instead of numeric accuracy (e.g., 90%). Furthermore, we observed scatterplots
    often assisted participants in validating their decisions. Based on the results, we
    believe that scatterplots and visualizations, in general, can aid in making informed
    decisions, validating decisions, and building trust in recommendation systems.}
}