JOURNAL ARTICLE
From Budgeting to Day Trading: A Content Analysis of Financial Advice on TikTok.
Published In: Journal of Financial Counseling & Planning, 2025, v. 36, n. 2. P. 315 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Gibson, Dominic J.; Tung, Allie; Chen, Katharine; Hoffman, Mikka; Castaneda, Lisa 3 of 3
Abstract
TikTok is a hugely popular social media platform among youth and young adults and is increasingly a source of information that goes beyond entertainment and social networking. In particular, the rise in financial advice on TikTok has been alternately hailed and fretted over as either a potentially valuable source of financial information for young people who may not have received formal financial education in school or a dangerous source of financial disinformation. However, there has not been any systematic description of the financial advice that is present on TikTok. Therefore, the current study pulled and categorized 120 TikTok videos (109 unique videos) containing financial advice to better understand what type of financial advice is typically offered on TikTok. We found a wide variety of financial advice on TikTok, but some types of financial advice (e.g., investment advice) were much more common than others. To an extent, the distribution of types of financial advice varied predictably according to the search terms used. Our findings provide a snapshot of the types of financial advice TikTok users are likely to encounter, which has implications for consumers' financial knowledge and decision-making. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Financial Counseling & Planning. 2025/08, Vol. 36, Issue 2, p315
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2025
- ISSN:1052-3073
- DOI:10.1891/JFCP-2023-0132
- Accession Number:187386821
- Copyright Statement:Copyright of Journal of Financial Counseling & Planning is the property of Springer Publishing Company, Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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