Emotional influences on user continuous use intention in recommended news apps: A study of algorithm appreciation and fatigue within the cognition-affect-conation framework

Based on the Cognition-Affect-Conation Model, this study explores the role of emotions in the relationship between users' perceptions and intention to continue using recommended news apps. TouTiao (recommended news application with the largest number of registered users in China) was chosen as...

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Main Authors: Ke Zhang, Yuchen Xie, Yutong He, Jing Wang
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Acta Psychologica
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S0001691825003154
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author Ke Zhang
Yuchen Xie
Yutong He
Jing Wang
author_facet Ke Zhang
Yuchen Xie
Yutong He
Jing Wang
author_sort Ke Zhang
collection DOAJ
description Based on the Cognition-Affect-Conation Model, this study explores the role of emotions in the relationship between users' perceptions and intention to continue using recommended news apps. TouTiao (recommended news application with the largest number of registered users in China) was chosen as the research object and a total of 1014 valid questionnaires were collected. The results based on mediation and moderation tests show that algorithm appreciation plays a mediating role among the perceived news value, the perceived recommendation personalization, the perceived recommendation explainability and the continuance usage intention. Algorithm fatigue plays a mediating role among users' perceived information narrowing, perceived content low quality, perceived information overload and continuance usage intention. Privacy concerns negatively moderate the positive effect of algorithm appreciation on continuance usage intention, while positively moderating the negative effect of algorithm fatigue on continuance usage intention. To enhance users' continuance usage intention recommended news apps, it is necessary to pay attention to the two emotional elements of algorithm appreciation and algorithm fatigue, thereby improving user experience, and achieving a win-win situation between the platform and users.
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institution OA Journals
issn 0001-6918
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publishDate 2025-06-01
publisher Elsevier
record_format Article
series Acta Psychologica
spelling doaj-art-c7f62425e7b2437fbcdac4b10a7e52ad2025-08-20T02:31:03ZengElsevierActa Psychologica0001-69182025-06-0125610500210.1016/j.actpsy.2025.105002Emotional influences on user continuous use intention in recommended news apps: A study of algorithm appreciation and fatigue within the cognition-affect-conation frameworkKe Zhang0Yuchen Xie1Yutong He2Jing Wang3School of Communication, Soochow University, Suzhou, Jiangsu, ChinaSchool of Communication, Soochow University, Suzhou, Jiangsu, ChinaSchool of Communication, Soochow University, Suzhou, Jiangsu, ChinaCity Culture and Communication College, Suzhou City University, Suzhou, Jiangsu, China.; Corresponding author.Based on the Cognition-Affect-Conation Model, this study explores the role of emotions in the relationship between users' perceptions and intention to continue using recommended news apps. TouTiao (recommended news application with the largest number of registered users in China) was chosen as the research object and a total of 1014 valid questionnaires were collected. The results based on mediation and moderation tests show that algorithm appreciation plays a mediating role among the perceived news value, the perceived recommendation personalization, the perceived recommendation explainability and the continuance usage intention. Algorithm fatigue plays a mediating role among users' perceived information narrowing, perceived content low quality, perceived information overload and continuance usage intention. Privacy concerns negatively moderate the positive effect of algorithm appreciation on continuance usage intention, while positively moderating the negative effect of algorithm fatigue on continuance usage intention. To enhance users' continuance usage intention recommended news apps, it is necessary to pay attention to the two emotional elements of algorithm appreciation and algorithm fatigue, thereby improving user experience, and achieving a win-win situation between the platform and users.http://www.sciencedirect.com/science/article/pii/S0001691825003154Algorithm perceptionAlgorithm appreciationAlgorithm fatiguePrivacy concernsCognition-affect-conation model
spellingShingle Ke Zhang
Yuchen Xie
Yutong He
Jing Wang
Emotional influences on user continuous use intention in recommended news apps: A study of algorithm appreciation and fatigue within the cognition-affect-conation framework
Acta Psychologica
Algorithm perception
Algorithm appreciation
Algorithm fatigue
Privacy concerns
Cognition-affect-conation model
title Emotional influences on user continuous use intention in recommended news apps: A study of algorithm appreciation and fatigue within the cognition-affect-conation framework
title_full Emotional influences on user continuous use intention in recommended news apps: A study of algorithm appreciation and fatigue within the cognition-affect-conation framework
title_fullStr Emotional influences on user continuous use intention in recommended news apps: A study of algorithm appreciation and fatigue within the cognition-affect-conation framework
title_full_unstemmed Emotional influences on user continuous use intention in recommended news apps: A study of algorithm appreciation and fatigue within the cognition-affect-conation framework
title_short Emotional influences on user continuous use intention in recommended news apps: A study of algorithm appreciation and fatigue within the cognition-affect-conation framework
title_sort emotional influences on user continuous use intention in recommended news apps a study of algorithm appreciation and fatigue within the cognition affect conation framework
topic Algorithm perception
Algorithm appreciation
Algorithm fatigue
Privacy concerns
Cognition-affect-conation model
url http://www.sciencedirect.com/science/article/pii/S0001691825003154
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