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  dataset_info:
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  features:
 
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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 RoBERTa models are linked as well.
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+ Argument component: Distinguishes the argumentative component that is used. Can be one of: claim, premise, background.
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+ Specificity: Differentiates between generic statements and more thoughtful user statements. Can be one of: general, specific, experience.
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+ Sentiment: A positive, balanced, negative or neutral argumentative statement about the reviewed item.
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+ Aspect: 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.
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  ---
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  dataset_info:
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  features: