From Hybrid Online User Reviews to Actionable Rankings: A Regret-Based Dynamic Model for Evaluating Mental Health Apps

Barcelona, Spain · May 2026

Posters · Digital Life & Emerging Technology in Psychology

Peter Darko Adjei
Zhejiang Normal University
Collins Opoku Antwi
Zhejiang Normal University
Baojing Zhang
Dongbu Junior Middle School
Baojing Zhang
Zhejiang Normal University
Evans Opoku-Mensah
Chengdu University of Technology
Daniel Baani Adjei
Presby Senior High Technical School

Abstract

Mental health apps generate massive, complex reviews that are difficult to translate into actionable evaluations. This study proposes a regret-based dynamic multi-attribute decision model integrating BERTopic-derived attributes, probabilistic reliable linguistic modeling, hybrid time-weighting, and a PRL-LAM ranking method to produce psychologically informed, time-sensitive rankings of apps using hybrid online reviews.

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From Hybrid Online User Reviews to Actionable Rankings: A Regret-Based Dynamic Model for Evaluating Mental Health Apps

Abstract

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