What question did this study set out to answer?

This article aims to theorize the influence of intelligent recommender systems on scholarly reading and information trajectories.

July 12, 2026Journal of Documentation

The impact of intelligent recommender systems in digital libraries on the structure of scholarly reading and users' information trajectories

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Authors

ESE. V. SamokhodkinState University of Management AEA. A. ElzonState University of Management

Discussion

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Implication

This integrative review reveals how recommender systems influence scholarly reading structures, indicating implications for visibility and academic identity.

Key Points

This article aims to theorize the influence of intelligent recommender systems on scholarly reading and information trajectories.
Conducted an integrative literature review from 2019 to 2025.
Analyzed national and international research on digital libraries and recommender systems.
Synthesized findings into a multi-level conceptual framework.
Recommender modules shape early-career researchers' identities at the micro level.
At the macro level, they introduce biases leading to visibility asymmetries in scholarly communication.
Developed a three-level model illustrating algorithmic feedback loops affecting user behavior and academic visibility.

Cite This Study

Samokhodkin et al. (2026) studied this question.

synapsesocial.com/papers/6a5332484f7abc118adedc7e https://doi.org/10.1108/jd-02-2026-0083

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July 12, 2026Journal of Documentation

The impact of intelligent recommender systems in digital libraries on the structure of scholarly reading and users' information trajectories

View Full Paper

Ask AI

Bookmark

Authors

ESE. V. SamokhodkinState University of Management AEA. A. ElzonState University of Management

Discussion

Member takes

Implication

This integrative review reveals how recommender systems influence scholarly reading structures, indicating implications for visibility and academic identity.

Key Points

This article aims to theorize the influence of intelligent recommender systems on scholarly reading and information trajectories.
Conducted an integrative literature review from 2019 to 2025.
Analyzed national and international research on digital libraries and recommender systems.
Synthesized findings into a multi-level conceptual framework.
Recommender modules shape early-career researchers' identities at the micro level.
At the macro level, they introduce biases leading to visibility asymmetries in scholarly communication.
Developed a three-level model illustrating algorithmic feedback loops affecting user behavior and academic visibility.

Cite This Study

Samokhodkin et al. (2026) studied this question.

synapsesocial.com/papers/6a5332484f7abc118adedc7e https://doi.org/10.1108/jd-02-2026-0083

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