Datasets:
Tasks:
Text Classification
Languages:
Portuguese
Multilinguality:
monolingual
Size Categories:
1M<n<10M
Language Creators:
other
License:
| # Copyright 2020 The HuggingFace Datasets Authors and the current dataset | |
| # script contributor. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """BPSAD -- Brazilian Portuguese Sentiment Analysis Datasets""" | |
| import csv | |
| import os | |
| import datasets | |
| import sys | |
| from datasets import ClassLabel | |
| csv.field_size_limit(sys.maxsize) | |
| _HOMEPAGE = """\ | |
| https://www.kaggle.com/datasets/fredericods/ptbr-sentiment-analysis-datasets""" | |
| _DESCRIPTION = """\ | |
| The Brazilian Portuguese Sentiment Analysis Dataset (BPSAD) is composed | |
| by the concatenation of 5 differents sources (Olist, B2W Digital, Buscapé, | |
| UTLC-Apps and UTLC-Movies), each one is composed by evaluation sentences | |
| classified according to the polarity (0: negative; 1: positive) and ratings | |
| (1, 2, 3, 4 and 5 stars).""" | |
| _CITATION = """\ | |
| @inproceedings{souza2021sentiment, | |
| author={ | |
| Souza, Frederico Dias and | |
| Baptista de Oliveira e Souza Filho, João}, | |
| booktitle={ | |
| 2021 IEEE Latin American Conference on | |
| Computational Intelligence (LA-CCI)}, | |
| title={ | |
| Sentiment Analysis on Brazilian Portuguese User Reviews}, | |
| year={2021}, | |
| pages={1-6}, | |
| doi={10.1109/LA-CCI48322.2021.9769838} | |
| } | |
| """ | |
| _VERSION = datasets.Version("1.0.0") | |
| _LICENSE = "" | |
| class BPSAD(datasets.GeneratorBasedBuilder): | |
| """BPSAD dataset.""" | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="polarity", | |
| description="Polarity classification dataset." | |
| ), | |
| datasets.BuilderConfig( | |
| name="rating", | |
| description="Rating classification dataset." | |
| ), | |
| ] | |
| def manual_download_instructions(self): | |
| return ( | |
| "To use this dataset you have to download it manually:\n" | |
| " 1. Download the `concatenated` file from `{_HOMEPAGE}`.\n" | |
| " 2. Extract the file inside `[PATH_TO_FILE]`.\n" | |
| " 3. Load the dataset using the command:\n" | |
| " datasets.load_dataset(" | |
| "\"lm4pt/bpsad\", name=..., data_dir=\"[PATH_TO_FILE]\")\n\n" | |
| "Possible names are: `polarity` and `rating`." | |
| ) | |
| def _info(self): | |
| # Note: | |
| # DEFAULT_CONFIG_NAME is not working and returns the value `default`. | |
| # Also, it is better to set the config name explicitly. | |
| if self.config.name not in ['polarity', 'rating']: | |
| raise ValueError(( | |
| f"`{self.config.name}` is not a valid config name. Possible " | |
| "values are `polarity` and `rating`. Make sure to pass via " | |
| "`datasets.load_dataset('lm4pt/bpsad', name=...)`" | |
| )) | |
| if self.config.name == "polarity": | |
| features = datasets.Features({ | |
| "review_text": datasets.Value("string"), | |
| "polarity": ClassLabel( | |
| num_classes=2, | |
| names=['negative', 'positive'] | |
| ), | |
| }) | |
| else: | |
| features = datasets.Features({ | |
| "review_text": datasets.Value("string"), | |
| "rating": datasets.Value("int8"), | |
| }) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION, | |
| license=_LICENSE, | |
| version=_VERSION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| data_dir = os.path.abspath(os.path.expanduser(dl_manager.manual_dir)) | |
| # validates if dataset folder exists | |
| if not os.path.exists(data_dir): | |
| raise FileNotFoundError(( | |
| data_dir + " does not exist. Make sure to pass the " | |
| "parameter `data_dir` via `datasets.load_dataset`.\n" | |
| "Manual download instructions:\n" + | |
| self.manual_download_instructions | |
| )) | |
| data_file = os.path.join(data_dir, "concatenated.csv") | |
| # check if dataset file exists | |
| if not os.path.exists(data_file): | |
| raise FileNotFoundError(( | |
| data_file + " does not exist. " + | |
| self.manual_download_instructions | |
| )) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": data_file, | |
| "split": "train", | |
| 'kfold_min': 1, | |
| 'kfold_max': 8 | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={ | |
| "filepath": data_file, | |
| "split": "dev", | |
| 'kfold_min': 9, | |
| 'kfold_max': 9 | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": data_file, | |
| "split": "test", | |
| 'kfold_min': 10, | |
| 'kfold_max': 10 | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath, split, kfold_min, kfold_max): | |
| # CSV columns | |
| # 0 - original_index, | |
| # 1 - review_text, | |
| # 2 - review_text_processed, | |
| # 3 - review_text_tokenized, | |
| # 4 - polarity, | |
| # 5 - rating, | |
| # 6 - kfold_polarity, | |
| # 7 - kfold_rating | |
| with open(filepath) as csv_file: | |
| csv_reader = csv.reader(csv_file, delimiter=',') | |
| # skip header | |
| _ = next(csv_reader) | |
| _id = 0 | |
| if self.config.name == 'polarity': | |
| for row in csv_reader: | |
| kfold = int(row[7]) | |
| if kfold_min <= kfold and kfold <= kfold_max: | |
| yield _id, { | |
| "review_text": row[2], | |
| "polarity": int(float(row[5])), | |
| } | |
| _id += 1 | |
| else: | |
| for row in csv_reader: | |
| kfold = int(row[8]) | |
| if kfold_min <= kfold and kfold <= kfold_max: | |
| yield _id, { | |
| "review_text": row[2], | |
| "rating": int(float(row[6])), | |
| } | |
| _id += 1 | |