"Sinhala YouTube Comments Imparting Knowledge to Society Through Humor"

"Sentiment Analysis (SA), also known as opinion mining is used to ascertain the sentiment or emotional undertone of a text. According to how strongly an opinion is held in favor of or against the subject matter being discussed, it can be categorized as either positive, negative, or objective. In the realm of SA, most research is mainly focused on the English language. According to the literature, the Sinhala Language gets minimal attention in the field of SA. The reason for that is that the Sinhala language is considered a morphologically rich but under-resourced language. YouTube is one of the most popular social media platforms with more than 2 billion users. It is also one of the platforms that contains a vast amount of text data. In the realm of SA, YouTube serves as an excellent source of such data. Understanding viewers' feelings and opinions about YouTube content will provide valuable insights to improve the quality and overall viewer experience of their future videos. In this study, 5000 amount of preprocessed comments were used from YouTube videos that impart knowledge to society through humor. That comment list was labeled as \u201cSatisfied\u201d, \u201cUnSatisfied\u201d, and \u201cOther\u201d. For the labeling process, two colleagues with expertise in the Sinhala language were involved to ensure labeling accuracy. Cohen\u2019s Kappa was calculated using the labeled comment list to determine the level of agreement between two annotators. The result was a Cohen\u2019s Kappa value of 0.457, indicating a moderate level of agreement. According to the study by Feng Yang et al., the final comment list of 3,680 was obtained by adopting the labels agreed upon by both annotators."