The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: FileNotFoundError
Message: Couldn't find a dataset script at /src/services/worker/katossky/multi-domain-sentiment/multi-domain-sentiment.py or any data file in the same directory. Couldn't find 'katossky/multi-domain-sentiment' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in katossky/multi-domain-sentiment.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 55, in compute_config_names_response
for config in sorted(get_dataset_config_names(path=dataset, token=hf_token))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1508, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at /src/services/worker/katossky/multi-domain-sentiment/multi-domain-sentiment.py or any data file in the same directory. Couldn't find 'katossky/multi-domain-sentiment' on the Hugging Face Hub either: FileNotFoundError: No (supported) data files or dataset script found in katossky/multi-domain-sentiment.Need help to make the dataset viewer work? Open a discussion for direct support.
This sentiment dataset was used in the paper: John Blitzer, Mark Dredze, Fernando Pereira. Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification. Association of Computational Linguistics (ACL), 2007.
The author asks, if you use this data for your research or a publication, to cite the above paper as the reference for the data, and to inform him about the reuse.
The Multi-Domain Sentiment Dataset contains product reviews taken from Amazon.com from 4 product types (domains): Kitchen, Books, DVDs, and Electronics. Each domain has several thousand reviews, but the exact number varies by domain. Reviews contain star ratings (1 to 5 stars) that can be converted into binary labels if needed.
The directory contains 3 files called positive.review, negative.review and unlabeled.review. While the positive and negative files contain positive and negative reviews, these aren't necessarily the splits the authors used in the experiments. They randomly drew from the three files ignoring the file names. Each file contains a pseudo XML scheme for encoding the reviews. Most of the fields are self explanatory. The reviews have a "unique ID" field that isn't very unique. If it has two unique id fields, ignore the one containing only a number.
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