Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
10K - 100K
ArXiv:
License:
Update tweet_topic_multi.py
Browse files- tweet_topic_multi.py +8 -2
tweet_topic_multi.py
CHANGED
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@@ -6,7 +6,7 @@ import datasets
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logger = datasets.logging.get_logger(__name__)
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_DESCRIPTION = """[TweetTopic](https://arxiv.org/abs/2209.09824)"""
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_VERSION = "1.0.
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_CITATION = """
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@inproceedings{dimosthenis-etal-2022-twitter,
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title = "{T}witter {T}opic {C}lassification",
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@@ -79,13 +79,19 @@ class TweetTopicSingle(datasets.GeneratorBasedBuilder):
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_key += 1
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"text": datasets.Value("string"),
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"date": datasets.Value("string"),
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"label": datasets.Sequence(datasets.
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"label_name": datasets.Sequence(datasets.Value("string")),
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"id": datasets.Value("string")
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}
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logger = datasets.logging.get_logger(__name__)
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_DESCRIPTION = """[TweetTopic](https://arxiv.org/abs/2209.09824)"""
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_VERSION = "1.0.4"
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_CITATION = """
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@inproceedings{dimosthenis-etal-2022-twitter,
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title = "{T}witter {T}opic {C}lassification",
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_key += 1
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def _info(self):
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names = [
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"arts_&_culture", "business_&_entrepreneurs", "celebrity_&_pop_culture", "diaries_&_daily_life", "family",
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"fashion_&_style", "film_tv_&_video", "fitness_&_health", "food_&_dining", "gaming",
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"learning_&_educational", "music", "news_&_social_concern", "other_hobbies", "relationships",
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"science_&_technology", "sports", "travel_&_adventure", "youth_&_student_life"
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]
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"text": datasets.Value("string"),
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"date": datasets.Value("string"),
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"label": datasets.Sequence(datasets.features.ClassLabel(names=names)),
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"label_name": datasets.Sequence(datasets.Value("string")),
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"id": datasets.Value("string")
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}
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