From influencers to lecturers: Understanding public attitudes toward digital vs. traditional jobs

The rapid expansion of high-speed internet has led to the emergence of new digital jobs, such as digital influencers, fitness models, and adult models who share content on subscription-based social media platforms. Across two experiments involving 1,002 participants, we combined theories from social psychology and information systems to investigate how digital jobs are perceived compared to matched established jobs, and predictors of attitudes toward those jobs (e.g., symbolic threat, contact, perceived usefulness). We found that individuals in digital professions were perceived as less favorably and less hard-working than those in matched established jobs. Digital jobs were also regarded as more threatening to societal values and less useful. The relation between job type and attitudes toward these jobs was partially mediated by contact with people working in these jobs, perceived usefulness, perception of hard work, and symbolic threat. These effects were consistent across both experiments, and consistent across various moderators: openness to new experiences, attitudes toward digitalization, political orientation, and age. Among the nine jobs examined, lecturers were perceived as most positive, while adult models were viewed as least positive. Overall, our findings demonstrate that integrating theories from social psychology and information systems can enhance our understanding of how attitudes are formed.

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Publication Details

Journal
Computers in Human Behavior Reports
Published
2026-04-01
DOI
https://doi.org/10.1016/j.chbr.2026.101046
Primary Topic
Cyberloafing and Workplace Behavior
Type
article
Field-Weighted Citation Impact
0.00
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article

From influencers to lecturers: Understanding public attitudes toward digital vs. traditional jobs

Jennifer Haase, Gabriel Lins de Holanda Coelho, Paul HP Hanel
Computers in Human Behavior Reports
Cyberloafing and Workplace Behavior
article

From influencers to lecturers: Understanding public attitudes toward digital vs. traditional jobs

Jennifer Haase, Gabriel Lins de Holanda Coelho, Paul HP Hanel
article en

Abstract

The rapid expansion of high-speed internet has led to the emergence of new digital jobs, such as digital influencers, fitness models, and adult models who share content on subscription-based social media platforms. Across two experiments involving 1,002 participants, we combined theories from social psychology and information systems to investigate how digital jobs are perceived compared to matched established jobs, and predictors of attitudes toward those jobs (e.g., symbolic threat, contact, perceived usefulness). We found that individuals in digital professions were perceived as less favorably and less hard-working than those in matched established jobs. Digital jobs were also regarded as more threatening to societal values and less useful. The relation between job type and attitudes toward these jobs was partially mediated by contact with people working in these jobs, perceived usefulness, perception of hard work, and symbolic threat. These effects were consistent across both experiments, and consistent across various moderators: openness to new experiences, attitudes toward digitalization, political orientation, and age. Among the nine jobs examined, lecturers were perceived as most positive, while adult models were viewed as least positive. Overall, our findings demonstrate that integrating theories from social psychology and information systems can enhance our understanding of how attitudes are formed.

Computers in Human Behavior ReportsVol. 22
University of Essex (GB), University College Cork (IE), Humboldt-Universität zu Berlin (DE), Weizenbaum Institute (DE)
Decent work and economic growth
Openalex Percentile: Top 29%
Cyberloafing and Workplace Behavior
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From influencers to lecturers: Understanding public attitudes toward digital vs. traditional jobs — Jennifer Haase, Gabriel Lins de Holanda Coelho, et al. · Computers in Human Behavior Reports (2026) | TGRS Research Map | TGRS