<![CDATA[YouTube is a very popular social media platform and is used by millions of people around the world. However, the presence of spam in comments can disrupt the user experience and affect the overall quality of the platform. Therefore, in this article, we conducted a Systematic Literature Review (SLR) to evaluate methods for detecting spam in comments on YouTube. In this SLR, we search for related research published between 2018 and 2023 in trusted databases such as Science Direct, IEEE Xplore, and Springer using Publish or Perish software. After making the selection, 17 of the 80 selected articles met our research criteria. The SLR results show that the Email dataset is the most widely used in spam detection research, and the most frequently used approach is supervised learning. In addition, most of the research focuses more on selecting features to improve accuracy in spam detection. The findings from this SLR can provide important insights for researchers who wish to conduct further research on spam detection on comments on YouTube.]]>
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