A Multiple Platforms dataset of 2,469,836 posts, 26,496,468 responses across 5 platforms, collected by Peixian and Zhang. Each record contains platform, posts, responses, op_gender, responder_gender, sentiment, relevance. Cumulative rtGender dataset combining all platforms for cross-platform gender analysis. Suitable for cross-platform gender analysis, sentiment comparison, response prediction.
A YouTube dataset of 2,004,605 comments from 635 videos, collected by Bwan Wando via YouTube API. Each record contains comment text, like count, reply count, video ID, timestamp, anonymized author ID. A large-scale dataset of 2M+ comments from the Wish 107.5 YouTube channel, a popular Philippine FM radio station known for its live music performances. Suitable for sentiment analysis, topic modeling, fan engagement, cultural studies, natural language processing.
A TED dataset of 0 posts, 190,414 responses, collected by Peixian and Zhang. Each record contains posts, responses, op_gender, responder_gender, sentiment, relevance. rtGender dataset for TED — studies gendered responses in online discourse. Suitable for gender studies, sentiment analysis, response prediction.
23,992 YouTube comments with sentiment and tone labels and short pros/cons notes, published on Hugging Face by AnandforU, in train (19,992), validation (2,000) and test (2,000) splits. Each record holds the comment text, sentiment, tone, pros and cons. Suitable for sentiment analysis and comment moderation.
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