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UXR Point of View on Product Feature Prioritization Prior To Multi-Million Engineering Commitments
Jonas Lau, Annie Tran
https://arxiv.org/abs/2506.15294 h…

UXR Point of View on Product Feature Prioritization Prior To Multi-Million Engineering Commitments
This paper discusses a popular UX research activity, feature prioritization, using the User Experience Research Point of View (UXR PoV) Playbook framework. We describe an application of multinomial logistic regression, frequently marketed as MaxDiff, for prioritizing product features in consumer product development. It addresses challenges of traditional surveying techniques. We propose a solution using MaxDiff to generate a reliable preference list with a reasonable sample size. We also adapt …

MCP-Orchestrated Multi-Agent System for Automated Disinformation Detection
Alexandru-Andrei Avram, Adrian Groza, Alexandru Lecu
https://arxiv.org/abs/2508.10143 https://

MCP-Orchestrated Multi-Agent System for Automated Disinformation Detection
The large spread of disinformation across digital platforms creates significant challenges to information integrity. This paper presents a multi-agent system that uses relation extraction to detect disinformation in news articles, focusing on titles and short text snippets. The proposed Agentic AI system combines four agents: (i) a machine learning agent (logistic regression), (ii) a Wikipedia knowledge check agent (which relies on named entity recognition), (iii) a coherence detection agent (u…

Understanding User Preferences for Interaction Styles in Conversational Recommender Systems: The Predictive Role of System Qualities, User Experience, and Traits
Raj Mahmud, Shlomo Berkovsky, Mukesh Prasad, A. Baki Kocaballi
https://arxiv.org/abs/2508.02328

Understanding User Preferences for Interaction Styles in Conversational Recommender Systems: The Predictive Role of System Qualities, User Experience, and Traits
Conversational Recommender Systems (CRSs) deliver personalised recommendations through multi-turn natural language dialogue and increasingly support both task-oriented and exploratory interactions. Yet, the factors shaping user interaction preferences remain underexplored. In this within-subjects study (\(N = 139\)), participants experienced two scripted CRS dialogues, rated their experiences, and indicated the importance of eight system qualities. Logistic regression revealed that preference f…