Evaluating narrative-driven movie recommendations on Reddit
summary
A dataset of 1,480 Reddit submissions is crowdsourced and released, five recommenders are implemented (item-based CF, matrix factorization, TF-IDF, doc2vec embeddings, actor–movie network), and a re-ranking pipeline uses IMDb metadata plus optional Reddit narrative tags. Adding the Reddit narratives yields the biggest gains — doc2vec and matrix factorization perform best and four methods beat the IMDb baseline by more than twofold, with up to 100% improvement; a reply bot prototype (rbzio) is under construction.
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chapters (6)
- 0:00Introduction
- 4:04Structured Input
- 6:31Post Filtering and REE Ranking
- 8:54Evaluation
- 11:18Summary
- 12:01Future work
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