task_categories:text-classification region:us
---
task_categories:
- text-classification

---
# AutoTrain Dataset for project: ta-winda-ota-sentiment-analysis

## Dataset Description

This dataset has been automatically processed by AutoTrain for project ta-winda-ota-sentiment-analysis.

### Languages

The BCP-47 code for the dataset's language is unk.

## Dataset Structure

### Data Instances

A sample from this dataset looks as follows:

```json
[
  {
    "feat_reviewId": "11e13237-0fe6-40ae-b035-e6d6d0287a80",
    "feat_userName": "Sulaiman",
    "feat_userImage": "https://play-lh.googleusercontent.com/a-/AD_cMMQbSKYMfa0BWeV5LYPf0kZ1MV3PKx_VgYzByqUb5Q",
    "text": "ok",
    "target": 4,
    "feat_thumbsUpCount": 0,
    "feat_reviewCreatedVersion": "3.77.1",
    "feat_at": "2023-05-27 01:49:05",
    "feat_replyContent": "Hi, we are so grateful to get a lot of support from you. Hope you continue to enjoy our offers. If you have any feedback or suggestions, let us know on https://www.traveloka.com/contactus, our customer service would love to serve you in 24 hours. Thank you!",
    "feat_repliedAt": "2023-05-27 02:12:14",
    "feat_appVersion": "3.77.1",
    "feat_sortOrder": "newest",
    "feat_appId": "com.traveloka.android"
  },
  {
    "feat_reviewId": "671f8bed-8371-490f-bc33-51034fc798f3",
    "feat_userName": "Feri Yadi",
    "feat_userImage": "https://play-lh.googleusercontent.com/a-/AD_cMMT7JhwvdqMkI84xvo_4HZ-2xV04Pvsn75E_SD3GoQ",
    "text": "ok",
    "target": 0,
    "feat_thumbsUpCount": 0,
    "feat_reviewCreatedVersion": "10.37.0",
    "feat_at": "2023-05-08 02:38:38",
    "feat_replyContent": "We apologize for any inconvenience this has caused you. Your experience is important to us. If there is something more we can help you with,\n\nplease write an email to googlesupport@agoda.com and include your phone number if you would prefer to be contacted by phone.\n\nOur team will review the information and contact you back as soon as possible.",
    "feat_repliedAt": "2023-05-08 05:14:09",
    "feat_appVersion": "10.37.0",
    "feat_sortOrder": "newest",
    "feat_appId": "com.agoda.mobile.consumer"
  }
]
```

### Dataset Fields

The dataset has the following fields (also called "features"):

```json
{
  "feat_reviewId": "Value(dtype='string', id=None)",
  "feat_userName": "Value(dtype='string', id=None)",
  "feat_userImage": "Value(dtype='string', id=None)",
  "text": "Value(dtype='string', id=None)",
  "target": "ClassLabel(names=['1', '2', '3', '4', '5'], id=None)",
  "feat_thumbsUpCount": "Value(dtype='int64', id=None)",
  "feat_reviewCreatedVersion": "Value(dtype='string', id=None)",
  "feat_at": "Value(dtype='string', id=None)",
  "feat_replyContent": "Value(dtype='string', id=None)",
  "feat_repliedAt": "Value(dtype='string', id=None)",
  "feat_appVersion": "Value(dtype='string', id=None)",
  "feat_sortOrder": "Value(dtype='string', id=None)",
  "feat_appId": "Value(dtype='string', id=None)"
}
```

### Dataset Splits

This dataset is split into a train and validation split. The split sizes are as follow:

| Split name   | Num samples         |
| ------------ | ------------------- |
| train        | 2826 |
| valid        | 709 |
