Interdisciplinary Studies in Media and Culture

The Algorithmic Process of Information Isolation Formation in Users’ Exposure to Political News on Instagram

Document Type : .

Authors

jahandar amiri 1
Amir mohammad zarqany 2

1 university faculty

2 university student

10.30465/ismc.2026.53460.3007
Abstract
Purpose: This study aimed to explain the process of filter bubble formation in users' encounters with political news on the Instagram platform, focusing on the dynamic interaction between the user, the algorithm, and the social network.

Method: The study was conducted using a qualitative method with a Grounded Theory approach. Data were collected through semi-structured interviews with 20 users and 6 experts, non-participant observation of profiles, and document analysis (comments). The data were analyzed using open, axial, and selective coding in MAXQDA software until theoretical saturation was achieved.

Findings: The findings led to the development of a "Tripartite Interaction Paradigmatic Model." This model demonstrates that the filter bubble forms through a reinforcing cycle resulting from the user's purposeful action (searching, following, and interacting), algorithmic reinforcement (suggestions, prioritization, and filtering), and the facilitating role of the social network (sharing and like-minded groups). The ultimate consequence of this process is the deepening of informational isolation, the reinforcement of confirmation bias, and the intensification of political polarization.

Conclusion: The r esults indicate that addressing the challenge of filter bubbles requires simultaneous intervention at three levels: "enhancing users' media literacy," "ensuring algorithmic transparency," and "considering the context of social networks."

Keywords

Filter Bubble
Instagram
Grounded Theory
Personalization
Algorithms
Subjects
Interdisciplinary Studies in Media and Culture
Volume 16, Issue 1 - Serial Number 31
1 (Spring& Summer)2026
September 2026

  • Receive Date 15 November 2025
  • Revise Date 10 June 2026
  • Accept Date 12 June 2026
  • Publish Date 23 August 2026

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