Datasets:

Languages:
English
Multilinguality:
monolingual
Size Categories:
n<1K
Language Creators:
found
Annotations Creators:
crowdsourced
Source Datasets:
original
License:
File size: 5,970 Bytes
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---
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- found
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: Opinosis
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- summarization
task_ids: []
paperswithcode_id: opinosis
tags:
- abstractive-summarization
dataset_info:
  features:
  - name: review_sents
    dtype: string
  - name: summaries
    sequence: string
  splits:
  - name: train
    num_bytes: 741270
    num_examples: 51
  download_size: 757398
  dataset_size: 741270
---

# Dataset Card for "opinosis"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** http://kavita-ganesan.com/opinosis-opinion-dataset/
- **Repository:** https://github.com/kavgan/opinosis-summarization
- **Paper:** [Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions](https://aclanthology.org/C10-1039/)
- **Point of Contact:** [Kavita Ganesan](mailto:kavita@opinosis.ai)
- **Size of downloaded dataset files:** 0.75 MB
- **Size of the generated dataset:** 0.74 MB
- **Total amount of disk used:** 1.50 MB

### Dataset Summary

The Opinosis Opinion Dataset consists of sentences extracted from reviews for 51 topics.
Topics and opinions are obtained from Tripadvisor, Edmunds.com and Amazon.com.

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### default

- **Size of downloaded dataset files:** 0.75 MB
- **Size of the generated dataset:** 0.74 MB
- **Total amount of disk used:** 1.50 MB

An example of 'train' looks as follows.
```
{
    "review_sents": "This is a fake topic. \nThe topics have multiple sentence inputs. \n",
    "summaries": ["This is a gold summary for topic 1. \nSentences in gold summaries are separated by newlines.", "This is another gold summary for topic 1. \nSentences in gold summaries are separated by newlines."]
}
```

### Data Fields

The data fields are the same among all splits.

#### default
- `review_sents`: a `string` feature.
- `summaries`: a `list` of `string` features.

### Data Splits

| name  |train|
|-------|----:|
|default|   51|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

The license for this dataset is Apache License 2.0 and can be found [here](https://github.com/kavgan/opinosis-summarization/blob/master/LICENSE).

### Citation Information

```
@inproceedings{ganesan2010opinosis,
  title={Opinosis: a graph-based approach to abstractive summarization of highly redundant opinions},
  author={Ganesan, Kavita and Zhai, ChengXiang and Han, Jiawei},
  booktitle={Proceedings of the 23rd International Conference on Computational Linguistics},
  pages={340--348},
  year={2010},
  organization={Association for Computational Linguistics}
}
```

### Contributions

Thanks to [@thomwolf](https://github.com/thomwolf), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.