A Dual-Annotated YouTube Comment Corpus on Precision Fermentation Technology (2019–2024)

This dataset contains 16,652 YouTube comments related to precision fermentation technology, collected via the YouTube Data API from 180 videos spanning February 2019 to November 2024. Each comment has been independently classified for sentiment (positive, negative, or neutral) by two models: GPT-4o (OpenAI) and EmoRoBERTa (a RoBERTa-based transformer fine-tuned on GoEmotions). The two models disagree on 39.1% of classifications, with EmoRoBERTa systematically underdetecting negative sentiment relative to GPT-4o. The deposit contains three files: human_annotated_subset.csv (n = 301): A subset with sentiment labels from both models plus a human annotator. Fields: VideoID, CommentID, Timestamp, GPT4o_Label, EmoRoBERTa_Label, Human_Label. full_corpus.csv (n = 16,652): The complete corpus with dual model annotations. Fields: VideoID, CommentID, Timestamp, Reply_Flag, GPT4o_Label, EmoRoBERTa_Label. codebook.txt: A plain-text codebook defining every variable in both data files, with value domains and notes on the timestamp format, rehydration, and the four hyphen-prefixed VideoIDs. Comment text is excluded to comply with YouTube API Developer Policies. Researchers may retrieve original comment text using the provided CommentIDs via the YouTube Data API. The data collection, preprocessing, and classification code is available at https://github.com/isom-ds/ffsp-sm-emotions.