A Quantitative Model to Evaluate Serendipity in Hypertext

• Main Authors: Yuri Kim, Bin Han, Jihyun Kim, Jisoo Song, Seoyeon Kang, Seongbin Park
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: Electronics
• Subjects: serendipity; information acquisition; evaluation model
• Online Access: https://www.mdpi.com/2079-9292/10/14/1678
• ISSN: 2079-9292

Serendipity is the phenomenon of people making unexpected and beneficial discoveries. While research on the mechanism and effectiveness of serendipity in information acquisition has been actively conducted, little attempt has been made to quantify serendipity when it occurs. In this paper, we present a quantitative model that measures serendipity experienced by users in a hypertext environment. In order to propose an evaluation model that measures how probable users would experience serendipitous moments in the process of an active search, we define a serendipitous discovery as an unexpected discovery that can happen during a sidetracked search. The proposed model consists of three parts: (a) pre-encountering—how early the user falls into the sidetracked search in the process of an active search; (b) post-encountering—the degree of interests of the entire process from the active search to obtaining unxpected information; and (c) discovery—the degree of the unexpectedness of the information obtained from the discovery. We evaluated the proposed model against examples with different structures and the potential serendipity values computed indicated the difference between the spaces in a meaningful way.