Context

This Dataset is an updated version of the Amazon review dataset released in 2014. As in the previous version, this dataset includes reviews (ratings, text, helpfulness votes), product metadata (descriptions, category information, price, brand, and image features), and links (also viewed/also bought graphs). In addition, this version provides the following features:

• More reviews:

  • The total number of reviews is 233.1 million (142.8 million in 2014).

• New reviews:

  • Current data includes reviews in the range May 1996 - Oct 2018.

• Metadata: - We have added transaction metadata for each review shown on the review page.

  • Added more detailed metadata of the product landing page.

Acknowledgements

If you publish articles based on this dataset, please cite the following paper:

• Jianmo Ni, Jiacheng Li, Julian McAuley. Justifying recommendations using distantly-labeled reviews and fined-grained aspects. EMNLP, 2019.

Amazon Review 2023 is an updated version of the Amazon Review 2018 dataset. This dataset mainly includes reviews (ratings, text) and item metadata (desc- riptions, category information, price, brand, and images). Compared to the pre- vious versions, the 2023 version features larger size, newer reviews (up to Sep 2023), richer and cleaner meta data, and finer-grained timestamps (from day to milli-second).

Dataset Card for Amazon Reviews 2018

This dataset is a collection of title-review pairs collected from Amazon, as collected in Ni et al.. See Amazon Reviews 2018 for additional information. This dataset can be used directly with Sentence Transformers to train embedding models.

  Dataset Subsets





  pair subset

Columns: "title", "review" Column types: str, str Examples:{ 'title': "It doesn't fit my machine. I can't seem to ...", 'review': "It doesn't fit my… See the full description on the dataset page: https://huggingface.co/datasets/sentence-transformers/amazon-reviews.

2 useful files:

1. all_categories.txt: 34 lines (33 categories + "Unknown"), each line contains a category name.
2. asin2category.json: A mapping between parent_asin (item ID) to its corresponding category name.

This is a large-scale Amazon Reviews dataset, collected in 2023 by McAuley Lab, and it includes rich features such as:

- User Reviews (ratings, text, helpfulness votes, etc.); - Item Metadata (descriptions, price, raw image, etc.); - Links (user-item / bought together graphs).

What's New? In the Amazon Reviews'23, we provide:

Larger Dataset: We collected 571.54M reviews, **245.2% **larger than the last version; - Newer Interactions: Current interactions range from May. 1996 to Sep. 2023; Richer Metadata: More descriptive features in item metadata; Fine-grained Timestamp: Interaction timestamp at the second or finer level; Cleaner Processing: Cleaner item metadata than previous versions; Standard Splitting: Standard data splits to encourage RecSys benchmarking.

Amazon Review Description Dataset

This dataset contains Amazon reviews from January 1, 2018, to June 30, 2018. It includes 2,245 sequences with 127,054 events across 18 category types. The original data is available at Amazon Review Data with citation information provided on the page. The detailed data preprocessing steps used to create this dataset can be found in the TPP-LLM paper and TPP-LLM-Embedding paper. If you find this dataset useful, we kindly invite you to cite the… See the full description on the dataset page: https://huggingface.co/datasets/tppllm/amazon-review-description.

Get the needed Amazon product review data right from the data extractor! Collect Amazon review information from 19 Amazon countries from the following domains: - amazon.com - amazon.com.au - amazon.com.br - amazon.ca - amazon.cn - amazon.fr - amazon.de - amazon.in - amazon.it - amazon.com.mx - amazon.nl - amazon.sg - amazon.es - amazon.com.tr

Request Ecommerce Product Review dataset by: - keyword - category - seller - product ID (ASIN)

Amazon E-commerce Reviews Data datasets gathered by keyword, seller, category, or ASIN contain: - Product ID (can be extended to the full product information) - Review content and rating - Review metadata

Amazon extraction results can be delivered by schedule or API request, so the data can be extracted in real-time.

DATAANT uses the in-house web scraping service with no concurrency limitations, so unlimited data extractions can be performed simultaneously.

Output can and attributes can be customized to fit your particular needs.

The displayed data on drivers for Amazon Prime usage shows results of an exclusive Statista survey conducted in the United States in 2018. Some ** percent of respondents answered the question ''What made you choose Amazon Video over other competitors?'' with ''Easier accessible / compatible with my devices''.The Survey Data Table for the Statista survey Tech Giants and Digital Services in the United States 2019 contains the complete tables for the survey including various column headings.

This dataset provides the complete catalog of point cloud data collected during LiDAR surveys over selected forest research sites across the Amazon rainforest in Brazil between 2008 and 2018 for the Sustainable Landscapes Brazil Project. Flight lines were selected to overfly key field research sites in the Brazilian states of Acre, Amazonas, Bahia, Goias, Mato Grosso, Para, Rondonia, Santa Catarina, and Sao Paulo. The point clouds have been georeferenced, noise-filtered, and corrected for misalignment of overlapping flight lines. They are provided in 1 km2 tiles. The data were collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time.

This dataset contains longitudinal purchases data from 5027 Amazon.com users in the US, spanning 2018 through 2022: amazon-purchases.csv It also includes demographic data and other consumer level variables for each user with data in the dataset. These consumer level variables were collected through an online survey and are included in survey.csv fields.csv describes the columns in the survey.csv file, where fields/survey columns correspond to survey questions. The dataset also contains the survey instrument used to collect the data. More details about the survey questions and possible responses, and the format in which they were presented can be found by viewing the survey instrument. A 'Survey ResponseID' column is present in both the amazon-purchases.csv and survey.csv files. It links a user's survey responses to their Amazon.com purchases. The 'Survey ResponseID' was randomly generated at the time of data collection. amazon-purchases.csv Each row in this file corresponds to an Amazon order. Each such row has the following columns: Survey ResponseID Order date Shipping address state Purchase price per unit Quantity ASIN/ISBN (Product Code) Title Category The data were exported by the Amazon users from Amazon.com and shared by users with their informed consent. PII and other information not listed above were stripped from the data. This processing occurred on users' machines before sharing with researchers.

Dataset

This dataset was created by Amina Ait Elkadi

Contents

"Amazon Strategic Review, 2018", offers comprehensive insight into the retailer, including in-depth analysis of: the hot issues driving its growth (its market-leading, tech-focused products which will drive loyalty, the continual development of its Amazon Prime proposition, the creation of original content which threatens Netflix’s hold on the streaming market, Amazon’s rapid expansion into food & grocery which is set to disrupt the sector, its prioritisation of market share growth in clothing and as Amazon’s marketing ramps up, how retailers must focus on ‘What Amazon Can’t Do’), its financial performance, its operating performance (overall and by sector) out to 2023e and consumer shopping habits. Read More

The displayed data on features of Amazon Prime by importance shows results of an exclusive Statista survey conducted in the United States in 2018. Some ** percent of respondents answered the question ''What are the most important prime account features for you?'' with ''Free premium delivery''.The Survey Data Table for the Statista survey Tech Giants and Digital Services in the United States 2019 contains the complete tables for the survey including various column headings.

The displayed data on the kind of the used Amazon account shows results of an exclusive Statista survey conducted in the United States in 2018. Some ** percent of respondents answered the question ''What kind of Amazon account do you have?'' with ''Basic account''.The Survey Data Table for the Statista survey Tech Giants and Digital Services in the United States 2019 contains the complete tables for the survey including various column headings.

Context

This dataset consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.

Contents

• Reviews.csv: Pulled from the corresponding SQLite table named Reviews in database.sqlite
  
• database.sqlite: Contains the table 'Reviews'
  
  

Data includes:
- Reviews from Oct 1999 - Oct 2012
- 568,454 reviews
- 256,059 users
- 74,258 products
- 260 users with > 50 reviews

Acknowledgements

See this SQLite query for a quick sample of the dataset.

If you publish articles based on this dataset, please cite the following paper:

• J. McAuley and J. Leskovec. From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews. WWW, 2013.

Dataset

This dataset was created by Ujjwal Malik

Contents

This dataset provides the complete catalog of forest inventory and biophysical measurements collected over selected forest research sites across the Amazon rainforest in Brazil between 2009 and 2018 for the Sustainable Landscapes Brazil Project. This dataset includes measurements for diameter at breast height (DBH), commercial tree height, and total tree height for forest inventories. Also included for each tree are the family, common and scientific names, coordinates, canopy position, crown radius, and for dead trees, the decomposition status. Aboveground biomass estimate is available for selected sites. The data are provided in comma-separated values (CSV) and shapefile formats. Sampling methodology for each site and year is described in companion files.

These datasets contain reviews from the Goodreads book review website, and a variety of attributes describing the items. Critically, these datasets have multiple levels of user interaction, raging from adding to a shelf, rating, and reading.

Metadata includes

• reviews

• add-to-shelf, read, review actions

• book attributes: title, isbn

• graph of similar books

Basic Statistics:

• Items: 1,561,465

• Users: 808,749

• Interactions: 225,394,930

This statistic displays the estimated revenues of books sold by Amazon in Italy from 2016 to 2018. According to data, in 2018 revenues have increased to 203 million euros.

Dataset

This dataset was created by Amina Ait Elkadi

Contents

The displayed data on attitudes towards Amazon shows results of an exclusive Statista survey conducted in the United States in 2018. Some ** percent of respondents answered the question ''Which of the following statements do you agree with regarding Amazon?'' with ''Amazon plays a pioneering role in this day and age.''.The Survey Data Table for the Statista survey Tech Giants and Digital Services in the United States 2019 contains the complete tables for the survey including various column headings.