通过社交媒体评论的层次化指标框架衡量智能手机用户体验
Measuring Smartphone User Experience through a Hierarchical Metric Framework via Social Media Reviews
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- Nankai University（南开大学）
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中文总结 AI 辅助
本研究提出层次化智能手机UX测量框架及可解释计算流程，将跨平台评论转化为结构化指标，应用于约2万条中文评论，实现跨品牌比较与指标级解释。
中文摘要 AI 辅助
智能手机用户体验（UX）广泛表达于跨平台的用户生成在线讨论中，为大规模真实环境下的测量创造了机会。然而，现有的UX工具和评论挖掘方法并未提供一种面向智能手机、基于理论的层次化测量规范，以支持跨异构平台的一致聚合与比较。在本研究中，我们提出了一种层次化的智能手机UX测量框架及一个可解释的计算流程，该流程将跨平台评论转化为结构化的UX指标。该流程提取局部化的体验证据单元，通过从粗到细的分类将其映射到层次结构中，并使用统一的五级满意度情感模型量化评价。我们将该方法应用于约20,000条中国社交媒体评论的分层子集，这些评论覆盖三个平台上的四个主要智能手机品牌。所得的指标将用户讨论的内容（通过归一化提及频率捕获）与用户如何评价该内容（通过平均五级情感得分捕获）区分开来。这项工作为跨品牌比较和指标级解释提供了一个可扩展且可解释的证据基础，超越了原始评论量或单一平台观察的局限。
英文摘要
Smartphone user experience (UX) is widely expressed in user-generated online discourse across platforms, creating opportunities for in-the-wild measurement at scale. However, existing UX instruments and review-mining approaches do not provide a smartphone-oriented, theory-grounded hierarchical measurement specification that supports consistent aggregation and comparison across heterogeneous platforms. In this research, we propose a hierarchical smartphone UX measurement framework and an interpretable computational pipeline that translates cross-platform reviews into structured UX metrics. The pipeline extracts localized experience evidence units, maps them to the hierarchy via coarse-to-fine classification, and quantifies evaluations with a unified five-level satisfaction sentiment model. We apply the approach to a stratified subset of approximately 20,000 Chinese social media reviews covering four major smartphone brands across three platforms. The resulting metrics separate what users discuss, captured by normalized mention frequency, from how they evaluate it, captured by mean five-level sentiment scores. This work provides a scalable and interpretable evidence base for cross-brand comparison and metric-level interpretation beyond raw review volume or single-platform observations.
