A scoping review of personalized user experiences on social media: The interplay between algorithms and human factors
Систематический обзор области персонализированного пользовательского опыта в социальных сетях: взаимодействие алгоритмов и человеческих факторов
2022-12-23
SCID: 54.1/jbgrjp4p
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algorithmic awarenessalgorithmic filteringcontent curationfilter bubblessocial media personalization
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Abstract (AI)
No social media user sees the same feed. These platforms are personalized to the individual with the aid of algorithms that filter and prioritize content based on users' demographic profiles and personal data. On the one hand, this personalization aids the user by making the service more relevant, for instance by curating information of interest. On the other hand, personalization introduces potential risks associated with privacy concerns, lack of autonomy and control, as well as limited diversity of information. This scoping review presents an overview of the current state of knowledge of social media personalization from different research domains, providing insight on social media users’ algorithmic awareness, their customization habits, their interactions with curated content, and the debate on how algorithms may create closed information outlets. It also provides a condensed overview of the different terminology used across domains, in the form of a glossary.
Key Findings
1
Algorithmic personalization creates risks involving privacy, reduced user autonomy and control, and limited exposure to diverse information.
2
Personalization can improve relevance by curating information aligned with users’ interests and needs.
3
Social media algorithms personalize individual feeds by filtering and prioritizing content according to demographic profiles and personal data.
4
The review consolidates terminology from multiple research domains into a glossary to clarify concepts surrounding social media personalization.
5
The scoping review synthesizes research on users’ algorithmic awareness, customization practices, interactions with curated content, and potentially closed information environments.
Research Object
personalized social media feeds and user experiences
Research Subject
the interplay of content-personalization algorithms and human factors, including algorithmic awareness, customization habits, interactions with curated content, and risks to privacy, autonomy, and information diversity
Publication Details
Publication Date
2022-12-23
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