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How Much Influencer Marketing is Undisclosed? Evidence from Twitter

Author

Listed:
  • Ershov, Daniel
  • He, Yanting
  • Seiler, Stephan

Abstract

We study the disclosure of influencer posts on Twitter across a large set of brands based on a unique data set of over 100 million posts and a novel classification method to detect undisclosed sponsorship. Using our preferred empirical specification we find that 96% of sponsored posts are not disclosed. This result is robust to a series of specification tests and even a lower bound classification still yield an undisclosed share of 82%. Despite stronger enforcement of disclosure regulations, the share of undisclosed posts decreases only slightly over time. Compared to disclosed posts, undisclosed posts tend to be associated with young brands with a large Twitter following. Using an online survey we find that many consumers are not able to identify sponsored content without disclosure. Our findings highlight a potential need for further regulatory scrutiny and suggest that researchers studying influencers must account for non-disclosed sponsored content.

Suggested Citation

  • Ershov, Daniel & He, Yanting & Seiler, Stephan, 2023. "How Much Influencer Marketing is Undisclosed? Evidence from Twitter," CEPR Discussion Papers 18554, Centre for Economic Policy Research.
    • Handle: RePEc:cpr:ceprdp:18554
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    More about this item

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising
    • M38 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Government Policy and Regulation

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