Leveraging ChatGPT for Sponsored Ad Detection and Keyword Extraction in Youtube Videos

This work-in-progress paper presents a novel approach to detecting sponsored advertisement segments in YouTube videos and comparing the advertisement with the main content. Our methodology involves the collection of 421 auto-generated and manual transcripts which are then fed into a prompt-engineered GPT-4o for ad detection, a KeyBERT for keyword extraction, and another iteration of ChatGPT for category identification. The results revealed a significant prevalence of product-related ads across various educational topics, with ad categories refined using GPT-4o into succinct 9 content and 4 advertisement categories. This approach provides a scalable and efficient alternative to traditional ad detection methods while offering new insights into the types and relevance of ads embedded within educational content. This study highlights the potential of LLMs in transforming ad detection processes and improving our understanding of advertisement strategies in digital media.

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Publication Details

Published
2024-12-18
DOI
https://doi.org/10.1109/i-coste63786.2024.11024962
Citations
1
Primary Topic
Advanced Text Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.35
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article

Leveraging ChatGPT for Sponsored Ad Detection and Keyword Extraction in Youtube Videos

Johnny Chan, Brice Valentin Kok-Shun
1 citations
Advanced Text Analysis Techniques
0.35
article

Leveraging ChatGPT for Sponsored Ad Detection and Keyword Extraction in Youtube Videos

Johnny Chan, Brice Valentin Kok-Shun
article en
1 citations

Abstract

This work-in-progress paper presents a novel approach to detecting sponsored advertisement segments in YouTube videos and comparing the advertisement with the main content. Our methodology involves the collection of 421 auto-generated and manual transcripts which are then fed into a prompt-engineered GPT-4o for ad detection, a KeyBERT for keyword extraction, and another iteration of ChatGPT for category identification. The results revealed a significant prevalence of product-related ads across various educational topics, with ad categories refined using GPT-4o into succinct 9 content and 4 advertisement categories. This approach provides a scalable and efficient alternative to traditional ad detection methods while offering new insights into the types and relevance of ads embedded within educational content. This study highlights the potential of LLMs in transforming ad detection processes and improving our understanding of advertisement strategies in digital media.

University of Auckland (NZ)
Openalex Percentile: Top 29%
Advanced Text Analysis Techniques
0.35
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Leveraging ChatGPT for Sponsored Ad Detection and Keyword Extraction in Youtube Videos — Johnny Chan, Brice Valentin Kok-Shun · (2024) | TGRS Research Map | TGRS