Quantifying the Nondisclosure of Influencer Advertising on Social Media

Daniel Ershov, Yanting He, and Stephan Seiler used a novel approach to identify undisclosed sponsored social media posts from text data, measuring the extent of advertising nondisclosure in a dataset composed of more than 100 million tweets. They found that over 96 percent of sponsored posts are undisclosed, constituting a pressing concern for regulators and practitioners.

Authors

Publication Details

Journal
Management and business review.
Published
2026-08-28
DOI
https://doi.org/10.1177/2694104x261479128
Primary Topic
Authorship Attribution and Profiling
Type
article
Field-Weighted Citation Impact
0.00
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article

Quantifying the Nondisclosure of Influencer Advertising on Social Media

Stephan Seiler, Daniel Ershov, Yanting He
Management and business review.
Authorship Attribution and Profiling
article

Quantifying the Nondisclosure of Influencer Advertising on Social Media

Stephan Seiler, Daniel Ershov, Yanting He
article en

Abstract

Daniel Ershov, Yanting He, and Stephan Seiler used a novel approach to identify undisclosed sponsored social media posts from text data, measuring the extent of advertising nondisclosure in a dataset composed of more than 100 million tweets. They found that over 96 percent of sponsored posts are undisclosed, constituting a pressing concern for regulators and practitioners.

Management and business review.Vol. 6(2-3)
Openalex Percentile: Top 8%
Authorship Attribution and Profiling
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Quantifying the Nondisclosure of Influencer Advertising on Social Media — Stephan Seiler, Daniel Ershov, et al. · Management and business review. (2026) | TGRS Research Map | TGRS