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ISMIE: A Framework to Characterize Information Seeking in Modern Information Environments

Shuoqi Sun, Danula Hettiachchi, Damiano Spina

TL;DR

ISMIE introduces an integrative framework to characterize information seeking in modern information environments by structuring three core concepts—Components, Intervening Variables, and Activities—into a formal, third-person analysis. It analyzes six existing IS/IR models, demonstrates gaps using a misinformation case study, and shows how ISMIE can guide both characterization and experimental design. The framework is then applied to misinformation dissemination, authenticity/trust crises in AI-generated content, and dopamine-driven consumption to illustrate actionable pathways and research blueprints. The authors emphasize future work on operationalizing ISMIE, integrating privacy and fairness considerations, and conducting empirical validation across diverse tasks, devices, and platforms. Overall, ISMIE offers a foundational vocabulary and analytical lens to understand human-system interactions in increasingly complex information ecosystems and to design rigorous studies and interventions accordingly.

Abstract

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.

ISMIE: A Framework to Characterize Information Seeking in Modern Information Environments

TL;DR

ISMIE introduces an integrative framework to characterize information seeking in modern information environments by structuring three core concepts—Components, Intervening Variables, and Activities—into a formal, third-person analysis. It analyzes six existing IS/IR models, demonstrates gaps using a misinformation case study, and shows how ISMIE can guide both characterization and experimental design. The framework is then applied to misinformation dissemination, authenticity/trust crises in AI-generated content, and dopamine-driven consumption to illustrate actionable pathways and research blueprints. The authors emphasize future work on operationalizing ISMIE, integrating privacy and fairness considerations, and conducting empirical validation across diverse tasks, devices, and platforms. Overall, ISMIE offers a foundational vocabulary and analytical lens to understand human-system interactions in increasingly complex information ecosystems and to design rigorous studies and interventions accordingly.

Abstract

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.

Paper Structure

This paper contains 44 sections, 2 figures, 1 table.

Table of Contents

  1. Introduction
  2. Proposed Framework: ISMIE
  3. Methodology
  4. Components in the ISMIE Framework
  5. Information Provider(s).
  6. Information Seeker(s).
  7. Information Seeking Actions.
  8. Presented Information.
  9. Variables in the Modern Information Environments
  10. Situational Variables (SitVar ).
  11. Personal Variables (PerVar ).
  12. Information Channel (InfoChan ).
  13. Interactive Variables (IntVar ).
  14. Cognitive Variables (CogVar ).
  15. Provider Attributes (ProAttr ).
  16. ...and 29 more sections

Figures (2)

  • Figure 1: The ISMIE framework (Section \ref{['sec:framework']}) for information seeking (IS) in modern information environments ().
  • Figure 2: Case study to illustrate the instantiation of variables (highlighted in colors). This scenario demonstrates the modern misinformation dissemination.