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metadata
language:
  - en
license:
  - cc-by-nc-4.0
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - sentiment-classification
dataset_info:
  features:
    - name: text
      dtype: string
    - name: inputs
      struct:
        - name: text
          dtype: string
    - name: prediction
      list:
        - name: label
          dtype: string
        - name: score
          dtype: float64
    - name: prediction_agent
      dtype: string
    - name: annotation
      dtype: 'null'
    - name: annotation_agent
      dtype: 'null'
    - name: multi_label
      dtype: bool
    - name: explanation
      dtype: 'null'
    - name: id
      dtype: string
    - name: metadata
      dtype: 'null'
    - name: status
      dtype: string
    - name: event_timestamp
      dtype: timestamp[us]
    - name: metrics
      struct:
        - name: text_length
          dtype: int64
  splits:
    - name: train
      num_bytes: 31840239
      num_examples: 20491
  download_size: 19678149
  dataset_size: 31840239

Dataset Card for "tripadvisor-hotel-reviews"

Dataset Description

Dataset Summary

Hotels play a crucial role in traveling and with the increased access to information new pathways of selecting the best ones emerged. With this dataset, consisting of 20k reviews crawled from Tripadvisor, you can explore what makes a great hotel and maybe even use this model in your travels! Citations on a scale from 1 to 5.

Languages

english

Citation Information

If you use this dataset in your research, please credit the authors. Citation Alam, M. H., Ryu, W.-J., Lee, S., 2016. Joint multi-grain topic sentiment: modeling semantic aspects for online reviews. Information Sciences 339, 206–223. DOI License CC BY NC 4.0 Splash banner

Contributions

Thanks to @davidberenstein1957 for adding this dataset.