How Relevance Feedback is Framed Affects User Experience, but not Behaviour

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http://hdl.handle.net/10138/313971

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Tripathi , D , Medlar , A & Glowacka , D 2019 , How Relevance Feedback is Framed Affects User Experience, but not Behaviour . in CHIIR'19 : Proceedings of the 2019 Conference on Human Information Interaction and Retrieval . ACM , New York, NY , pp. 307-311 , ACM SIGIR Conference on Human Information Interaction and Retrieval , Glasgow , United Kingdom , 10/03/2019 . https://doi.org/10.1145/3295750.3298957

Title: How Relevance Feedback is Framed Affects User Experience, but not Behaviour
Author: Tripathi, Dhruv; Medlar, Alan; Glowacka, Dorota
Contributor: University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
Publisher: ACM
Date: 2019
Language: eng
Number of pages: 5
Belongs to series: CHIIR'19 Proceedings of the 2019 Conference on Human Information Interaction and Retrieval
ISBN: 978-1-4503-6025-8
URI: http://hdl.handle.net/10138/313971
Abstract: Retrieval systems based on machine learning require both positive and negative examples to perform inference, which is usually obtained through relevance feedback. Unfortunately, explicit negative relevance feedback is thought to have poor user experience. Instead, systems typically rely on implicit negative feedback. In this study, we confirm that, in the case of binary relevance feedback, users prefer giving positive feedback ( and implicit negative feedback) over negative feedback ( and implicit positive feedback). These two feedback mechanisms are functionally equivalent, capturing the same information from the user, but differ in how they are framed. Despite users' preference for positive feedback, there were no significant differences in behaviour. As users were not shown how feedback influenced search results, we hypothesise that previously reported results could, at least in part, be due to cognitive biases related to user perception of negative feedback.
Subject: relevance feedback
negative relevance feedback
user studies
experimental design
scientific literature search
RETRIEVAL
CBIR
113 Computer and information sciences
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