Who’s Afraid of the Big Bad Lurker? Lurking, AI, and Social Media Literacies

This paper identifies the trajectory of literature on the concept of lurking and uses key examples from this development to suggest their usefulness to Social Media Literacies (SML). Although itself a relatively new area, SML scholars have argued for the need to prioritise critical thinking over usability of social media platforms (McWhirter, 2024). An idea often ignored in much digital and social media research is that of lurking. But can this concept be of use to the newly developing area of SML? Can Artificial Intelligence (AI) research tools uncover not only developments in the conceptual thinking on lurking scholarship but also identify key ideas that help to support the argument for lurking as a key frame for SML? The work explores the evolution of the concept of the lurker over the past three decades and argues that the idea is an important lens onto the digital world. Lurking is broadly representative of a silent majority in online spaces where most users are not (always) creating, reacting to, or sharing content. Sipley (2024) highlights the negative history of the lurker, calls for more attention to be brought to this phenomenon, and questions the developmental thinking on the concept. This research uses different types of AI to sort and synthesise conceptual literature on lurking from 2000 to 2024, finding that much developmental thinking has occurred, moving the debate beyond simplistic “posters versus lurkers” contexts. The paper reflects on the usefulness of AI research assistants – such as ASReview Lab and NotebookLM – in distilling and analysing conceptual ideas about lurkers and lurking. These tools quickly uncover work that develops the lurker idea and highlight key papers. In turn these concepts are explored with their relevance to SML, from an awareness of behaviours in online contexts, to social media research methods, to surveillance capitalism.

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Publication Details

Journal
European Conference on Social Media
Published
2025-05-20
DOI
https://doi.org/10.34190/ecsm.12.1.3368
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Who’s Afraid of the Big Bad Lurker? Lurking, AI, and Social Media Literacies

Andrew McWhirter
European Conference on Social Media
AI in Service Interactions
article

Who’s Afraid of the Big Bad Lurker? Lurking, AI, and Social Media Literacies

Andrew McWhirter
article en

Abstract

This paper identifies the trajectory of literature on the concept of lurking and uses key examples from this development to suggest their usefulness to Social Media Literacies (SML). Although itself a relatively new area, SML scholars have argued for the need to prioritise critical thinking over usability of social media platforms (McWhirter, 2024). An idea often ignored in much digital and social media research is that of lurking. But can this concept be of use to the newly developing area of SML? Can Artificial Intelligence (AI) research tools uncover not only developments in the conceptual thinking on lurking scholarship but also identify key ideas that help to support the argument for lurking as a key frame for SML? The work explores the evolution of the concept of the lurker over the past three decades and argues that the idea is an important lens onto the digital world. Lurking is broadly representative of a silent majority in online spaces where most users are not (always) creating, reacting to, or sharing content. Sipley (2024) highlights the negative history of the lurker, calls for more attention to be brought to this phenomenon, and questions the developmental thinking on the concept. This research uses different types of AI to sort and synthesise conceptual literature on lurking from 2000 to 2024, finding that much developmental thinking has occurred, moving the debate beyond simplistic “posters versus lurkers” contexts. The paper reflects on the usefulness of AI research assistants – such as ASReview Lab and NotebookLM – in distilling and analysing conceptual ideas about lurkers and lurking. These tools quickly uncover work that develops the lurker idea and highlight key papers. In turn these concepts are explored with their relevance to SML, from an awareness of behaviours in online contexts, to social media research methods, to surveillance capitalism.

European Conference on Social MediaVol. 12(1)
Glasgow Caledonian University (GB)
Openalex Percentile: Top 95%
AI in Service Interactions
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