{"url":"/dataset/multisenti","name":"MultiSenti","full_name":null,"description_markdown":"MultiSenti presents a labeled dataset called MultiSenti for sentiment classification of code-switched informal short text, (2) explore the feasibility of adapting resources from a resource-rich language for an informal one, and (3) propose a deep learning-based model for sentiment classification of code-switched informal short text.\r\n\r\nSource: [Adapting Deep Learning for Sentiment Classification of Code-Switched Informal Short Text](/paper/adapting-deep-learning-for-sentiment)","description_withheld":null,"homepage":"https://github.com/haroonshakeel/multisenti","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/adapting-deep-learning-for-sentiment","title":"Adapting Deep Learning for Sentiment Classification of Code-Switched Informal Short Text","first_author":"Muhammad Haroon Shakeel","url":null},"license":null,"modalities":[],"tasks":[{"name":"Sentiment Analysis","url":"/task/sentiment-analysis","datasets_with_task":"/datasets/task/sentiment-analysis"},{"name":"Lexical Normalization","url":"/task/lexical-normalization","datasets_with_task":"/datasets/task/lexical-normalization"}],"languages":[],"variants":["MultiSenti"],"data_loaders":[{"repo":"https://github.com/haroonshakeel/multisenti","url":"https://github.com/haroonshakeel/multisenti","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":"2026-09-24T18:15:14+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."}