size_categories:10K<n<100K language:en recommendation conversational recommendation sentiment analysis arxiv:1812.07617 region:us
---
dataset_info:
- config_name: SA
  features:
    - name: movieId
      dtype: int32
    - name: movieName
      dtype: string
    - name: messages
      sequence: string
    - name: senders
      sequence: int32
    - name: form
      sequence: int32
  splits:
    - name: train
      num_bytes: 33174059
      num_examples: 41370
    - name: validation
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      num_examples: 10329
    - name: test
      num_bytes: 5151856
      num_examples: 6952
  download_size: 32552755
  dataset_size: 46550509
- config_name: rec
  features:
  - name: movieIds
    sequence: int32
  - name: messages
    sequence: string
  - name: senders
    sequence: int32
  splits:
  - name: train
    num_bytes: 6064195
    num_examples: 8004
  - name: validation
    num_bytes: 1511644
    num_examples: 2002
  - name: test
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    num_examples: 1342
  download_size: 4812520
  dataset_size: 8513578
- config_name: autorec
  features:
    - name: movieIds
      sequence: int32
    - name: ratings
      sequence: float32
  splits:
    - name: train
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      num_examples: 7840
    - name: validation
      num_bytes: 87496
      num_examples: 1966
    - name: test
      num_bytes: 58704
      num_examples: 1321
  download_size: 32552755
  dataset_size: 496888
config_names:
- SA
- rec
- autorec
tags:
- recommendation
- conversational recommendation
- sentiment analysis
language:
- en
pretty_name: ReDIAL
size_categories:
- 10K<n<100K
---

# Dataset Card for ReDIAL

## Dataset Description

- **Homepage:** 
- **Repository:** 
 [RecBot](https://github.com/McAuley-Lab/RecBot).
- **Paper:** 
- **Leaderboard:** 
- **Point of Contact:** 

### Dataset Summary

This is an adapted version of the [original redial dataset](https://huggingface.co/datasets/re_dial), for supporting different tasks in our project [RecBot](https://github.com/McAuley-Lab/RecBot).
The redial dataset provides over 10,000 conversations centered around movie recommendations. It was released in the paper ["Towards Deep Conversational Recommendations"](https://arxiv.org/abs/1812.07617) at NeurIPS 2018.

### Supported Tasks and Leaderboards
1. Sentiment Analysis: Use the SA config for sentiment analysis. 
2. Recommendation: Use the autorec config for recommendation task.
3. Conversational recommendation: Use the rec config for conversational recommendation task.

### Languages

English

## Dataset Structure

### Data Instances

#### SA


An example of 'test' looks as follows.
```
{
  "movieId": 111776,
  "movieName": "Super Troopers",
  "messages": [
    "Hi I am looking for a movie like @111776",
    "You should watch @151656",
    "Is that a great one? I have never seen it. I have seen @192131\nI mean @134643",
    "Yes @151656 is very funny and so is @94688",
    "It sounds like I need to check them out",
    "yes you will enjoy them",
    "I appreciate your time. I will need to check those out. Are there any others you would recommend?",
    "yes @101794",
    "Thank you i will watch that too",
    "and also @91481",
    "Thanks for the suggestions.",
    "you are welcome\nand also @124771",
    "thanks goodbye"
  ],
  "senders": [1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1],
  "form": [0, 1, 1, 0, 1, 1]
}
```

#### rec
An example of 'test' looks as follows.
```
{
  'movieIds': [111776, 91481, 151656, 134643, 192131, 124771, 94688, 101794],
  'messages': ['Hi I am looking for a movie like @111776',
    'You should watch @151656',
    'Is that a great one? I have never seen it. I have seen @192131\nI mean @134643',
    'Yes @151656 is very funny and so is @94688',
    'It sounds like I need to check them out',
    'yes you will enjoy them',
    'I appreciate your time. I will need to check those out. Are there any others you would recommend?',
    'yes @101794',
    'Thank you i will watch that too',
     'and also @91481',
    'Thanks for the suggestions.',
    'you are welcome\nand also @124771',
    'thanks goodbye'],
  'senders': [1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1]
}
```

#### autorec
An example of 'test' looks as follows.
```
{
  "movieIds": [
    111776,
    151656,
    134643,
    192131,
    94688
  ],
  "ratings": [
    1.0,
    1.0,
    1.0,
    1.0,
    1.0
  ]
}
```


### Data Fields
#### SA
- movieId: the movie's ID in the [MovieLens](https://grouplens.org/datasets/movielens/latest/) dataset.
- movieName: the movie's name.
- messages: a list of string. The conversation messages related to the movie. Note that one conversation can contain mutiple movies. The conversation messages are repeated for each movie as a sample.
- senders: a list of 1 or -1. It has the same length of messages. Each element indicates the message at the same index is from the initiatorWorker (with 1) or the respondentWorkerId (with -1).
- form: a list generated by: [init_q[movieId]["suggested"], init_q[movieId]["seen"], init_q[movieId]["liked"], resp_q[movieId]["suggested"], resp_q[movieId]["seen"], resp_q[movieId]["liked"]. init_q is the initiator questions in the conversation. resp_q is the respondent questions in the conversation.

#### rec
- movieIds: a list of movie ids in a conversation.
- messages: a list of string. see config SA for detail.
- senders: a list of 1 or -1. see config SA for detail.

#### autorec:
- movieIds: a list of movie ids in a conversation.
- ratings: a list of 0 or 1. It has the same length as movieIds. Each element indicates the inititator's "liked" value for the movie.

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]