This dataset contain online reviews gathered from google reviews written by north american casino users. explain motivations and summary of its content. Can be used to study user experience and relative research directions such as cultural impacts on latency of aspects, domain importance, sentiment analysis, opinion mining, aspect-based sentiment analysis, etc.
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Sentiment analysis is increasingly viewed as a vital task both from an academic and a commercial standpoint. The majority of current approaches, however, attempt to detect the overall polarity of a sentence, paragraph, or text span, regardless of the entities mentioned (e.g., laptops, restaurants) and their aspects (e.g., battery, screen; food, service). By contrast, this task is concerned with aspect based sentiment analysis (ABSA), where the goal is to identify the aspects of given target entities and the sentiment expressed towards each aspect. Datasets consisting of customer reviews with human-authored annotations identifying the mentioned aspects of the target entities and the sentiment polarity of each aspect will be provided.
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YASO is a crowd-sourced TSA evaluation dataset, collected using a new annotation scheme for labeling targets and their sentiments. The dataset contains 2,215 English sentences from movie, business and product reviews, and 7,415 terms and their corresponding sentiments annotated within these sentences.
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The Yelp Dataset is a valuable resource for academic research, teaching, and learning. It provides a rich collection of real-world data related to businesses, reviews, and user interactions. Here are the key details about the Yelp Dataset: Reviews: A whopping 6,990,280 reviews from users. Businesses: Information on 150,346 businesses. Pictures: A collection of 200,100 pictures. Metropolitan Areas: Data from 11 metropolitan areas. Tips: Over 908,915 tips provided by 1,987,897 users. Business Attributes: Details like hours, parking availability, and ambiance for more than 1.2 million businesses. Aggregated Check-ins: Historical check-in data for each of the 131,930 businesses.
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