{"url":"/dataset/user-reviews-and-perfume-attributes-dataset","name":"Perfume Co-Preference Network","full_name":null,"description_markdown":"The **Perfume Co-Preference Network ** dataset comprises comprehensive user reviews and ratings collected from the Persian retail platform Atrafshan. This dataset, central to our research on community detection in fragrance preferences, includes **36,434 comments** from **7,387 unique users**, providing insights into consumer sentiment towards various perfumes. It is designed to facilitate the analysis of user preferences through sentiment analysis, allowing for the clustering of perfumes based on shared attributes.\r\n\r\nThe dataset features three main components:\r\n\r\n1. **User Reviews and Perfume Attributes Dataset**: This captures user sentiments expressed in comments, along with metadata such as user IDs, perfume details, and ratings across key attributes (scent, longevity, sillage, and design).\r\n  \r\n2. **Emoji Mapping Dataset**: This includes **392 common emojis** mapped to their Persian equivalents to enhance sentiment analysis accuracy.\r\n\r\n3. **Sentiment Classification Results**: This section includes three CSV files that detail sentiment classifications biased toward specific perfume attributes: **Scent**, **Longevity**, and **Sillage**. These classifications are derived from user comments using the ParsBert model, integrating user ratings to provide a nuanced understanding of consumer preferences.\r\n\r\nFor access to the dataset and further details, please visit our [GitHub repository](https://github.com/Kalashi-Saed-Collaborations/SentimentDrivenCommunityDetection).\r\n\r\n**Total number of user comments:** 36,434  \r\n**Total number of unique users:** 7,387  \r\n**Number of emojis in mapping:** 392  \r\n**Number of CSV files with sentiment classifications:** 3","description_withheld":null,"homepage":"","introduced_date":"2024-10-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/sentiment-driven-community-detection-in-a","title":"Sentiment-Driven Community Detection in a Network of Perfume Preferences","first_author":"Kamand Kalashi","url":null},"license":{"name":"CC BY","url":"https://creativecommons.org/licenses/by/4.0/"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Graphs","url":"/datasets/modality/graphs"},{"name":"Tables","url":"/datasets/modality/tables"}],"tasks":[{"name":"Community Detection","url":"/task/community-detection","datasets_with_task":"/datasets/task/community-detection"},{"name":"Graph Clustering","url":"/task/graph-clustering","datasets_with_task":"/datasets/task/graph-clustering"},{"name":"Network Community Partition","url":"/task/network-community-partition","datasets_with_task":"/datasets/task/network-community-partition"},{"name":"graph construction","url":"/task/graph-construction","datasets_with_task":"/datasets/task/graph-construction"},{"name":"Persian Sentiment Analysis","url":"/task/persian-sentiment-anlysis","datasets_with_task":"/datasets/task/persian-sentiment-anlysis"},{"name":"Sentiment Classification","url":"/task/sentiment-classification","datasets_with_task":"/datasets/task/sentiment-classification"}],"languages":[{"name":"English","url":"/datasets/language/english"},{"name":"Persian","url":"/datasets/language/persian"},{"name":"Iranian Persian","url":"/datasets/language/iranian-persian"}],"variants":["Perfume Co-Preference Network"],"data_loaders":[{"repo":"https://github.com/Kalashi-Saed-Collaborations/SentimentDrivenCommunityDetection","url":"https://github.com/Kalashi-Saed-Collaborations/SentimentDrivenCommunityDetection","frameworks":[]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}