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--- |
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dataset_info: |
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features: |
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- name: type |
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dtype: string |
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- name: text |
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dtype: string |
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- name: annotator |
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dtype: string |
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- name: component |
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dtype: string |
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- name: specificity |
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dtype: string |
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- name: sentiment |
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dtype: string |
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- name: aspect |
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dtype: string |
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- name: id |
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dtype: string |
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- name: sidx |
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dtype: float64 |
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splits: |
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- name: train |
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num_bytes: 1328357 |
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num_examples: 7266 |
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download_size: 534609 |
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dataset_size: 1328357 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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# Dataset Card for "argureviews" |
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Dataset for basic argumentation in online reviews |
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The dataset aims to annotate online review sentences for basic argumentative quality, sentiment and aspect of interest. It covers 1016 online reviews with 7286 sentences for the following domains: products from Amazon, local services, restaurant and hotels from Yelp and brokerage apps from the Google Play Store. |
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The label set descriptions are as follows. The respective DeBERTa models are linked as well. |
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- [Argument component](/nihiluis/argureviews-component-deberta_v1): Distinguishes the argumentative component that is used. Can be one of: claim, premise, background. |
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- [Specificity](/nihiluis/argureviews-specificity-deberta_v1): Differentiates between generic statements and more thoughtful user statements. Can be one of: general, specific, experience. |
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- [Sentiment](/nihiluis/argureviews-sentiment-deberta_v1): A positive, balanced, negative or neutral argumentative statement about the reviewed item. |
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- [Aspect](/nihiluis/argureviews-aspect-deberta_v1): Provides more insight into what aspect of interest the argumentative statement covers. Can be one or more of: general sentiment, price, delivery, function and quality, fun and usage, style, installation, customer service and none. Only available for the Amazon review subset. |
