提出ISMIE框架，系统解析现代信息环境下的信息搜索行为。
ISMIE: A Framework to Characterize Information Seeking in Modern Information Environments
- 以三大概念构建信息搜索过程模型：主体、中介变量与活动。
- 通过假信息传播案例，揭示现有模型在复杂环境中的局限性。
- 提供用户与系统双重视角的研究设计蓝图，适配学术与产业需求。
现代信息环境（MIE）日益复杂，由多种技术共同塑造，旨在满足用户的多样化信息需求。信息寻求（IS）模型是表征用户与系统交互的有效机制，但全面刻画MIE景观的模型仍面临挑战。本文提出信息寻求在现代信息环境（ISMIE）框架，作为基础性探索。该框架通过三个核心概念——主体（如信息寻求者）、中介变量（如交互变量）和活动（如获取）——构建信息寻求过程（ISP）的理论模型。基于假信息传播这一典型场景，我们分析了六个现有的信息寻求与信息检索（IR）模型，揭示其在复杂环境中的不足，并论证了构建ISMIE框架的必要性。进一步，我们展示了该框架在表征与实验设计中的可操作性，识别出三项紧迫问题，并提出两种研究蓝图：一是面向用户、产业驱动的实验设计，应对人工智能生成内容的可信度与信任危机；二是面向系统、学术驱动的设计，用于缓解多巴胺驱动的内容消费现象。本框架为发展更先进的信息寻求与信息检索模型提供了理论基础，助力理解人类互动与系统设计在现代信息环境中的演进。
原文摘要 · Abstract (English)
The modern information environment (MIE) is increasingly complex, shaped by a wide range of techniques designed to satisfy users' information needs. Information seeking (IS) models are effective mechanisms for characterizing user-system interactions. However, conceptualizing a model that fully captures the MIE landscape poses a challenge. We argue: Does such a model exist? To address this, we propose the Information Seeking in Modern Information Environments (ISMIE) framework as a fundamental step. ISMIE conceptualizes the information seeking process (ISP) via three key concepts: Components (e.g., Information Seeker), Intervening Variables (e.g., Interactive Variables), and Activities (e.g., Acquiring). Using ISMIE's concepts and employing a case study based on a common scenario - misinformation dissemination - we analyze six existing IS and information retrieval (IR) models to illustrate their limitations and the necessity of ISMIE. We then show how ISMIE serves as an actionable framework for both characterization and experimental design. We characterize three pressing issues and then outline two research blueprints: a user-centric, industry-driven experimental design for the authenticity and trust crisis to AI-generated content and a system-oriented, academic-driven design for tackling dopamine-driven content consumption. Our framework offers a foundation for developing IS and IR models to advance knowledge on understanding human interactions and system design in MIEs.
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