IRAIHCJul 16, 2018

Human Perception of Surprise: A User Study

arXiv:1807.05906v1
Originality Synthesis-oriented
AI Analysis

This work addresses the problem of user engagement for applications like learning and entertainment, but it is incremental as it builds on existing research about surprise and attention.

The study investigated how people and algorithms rank the surprisingness of facts, finding through a crowdsourcing study with 106 participants that computational models of surprise can artificially induce surprise in humans.

Understanding how to engage users is a critical question in many applications. Previous research has shown that unexpected or astonishing events can attract user attention, leading to positive outcomes such as engagement and learning. In this work, we investigate the similarity and differences in how people and algorithms rank the surprisingness of facts. Our crowdsourcing study, involving 106 participants, shows that computational models of surprise can be used to artificially induce surprise in humans.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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