Machine learning approach to auto-tagging online content for content marketing efficiency: A comparative analysis between methods and content type
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AI can automatically create digital content using existing digital content as its source.
“Third, AI can automatically create digital content (e.g., texts, news, essays, images) using existing digital content as its source (Salminen et al., 2019).”
From Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world (2023) · cites this paper as Salminen et al., 2019
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Cited by
Sorted by citations
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- Authors
- Salminen, J., Yoganathan, V., Corporan, J., Jansen, B. J., & Jung, S.-G.
- Affiliations
- University of Turku (FI)
- University of Bradford (GB)
- Hamad bin Khalifa University (QA)
- Corresponding author
- Yoganathan, Vignesh
- Venue
- Journal of Business Research
- Publisher
- Elsevier BV
- Published
- 2019-08
- Volume
- 101
- Pages
- 203-217
- ISSN
- 0148-2963 (ISSN-L)
- OpenAlex
- W2941195982
- Cited by
- 99
- References
- 54
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 16 · 2023: 18 · 2022: 19 · 2021: 17 · 2020: 15 · 2019: 1
- FWCI
- 6.00
- Type
- journal article
- Language
- en
- Open access
- green
- www.utupub.fi
- Locations
- Journal of Business Research (publishedVersion)
- UTUPub (University of Turku) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Bradford Scholars (University of Bradford) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
- Social Sciences › General Social Sciences › Computational and Text Analysis Methods
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Keywords
- multi-label classification, content marketing, online news articles, YouTube content, random forest, k-nearest neighbors, artificial neural networks, cross-platform validation, unstructured data
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