README.md

---
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 1k<10K
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: TweetNER7
---

# Dataset Card for "tner/tweetner7"

## Dataset Description

- **Repository:** [https://github.com/asahi417/tner/tree/master/examples/tweetner7_paper](https://github.com/asahi417/tner/tree/master/examples/tweetner7_paper)
- **Paper:** TBA
- **Dataset:** TweetNER7
- **Domain:** Twitter
- **Number of Entity:** 7


### Dataset Summary
This is an official of TweetNER7 ("Named Entity Recognition in Twitter:
A Dataset and Analysis on Short-Term Temporal Shifts, AACL main conference 2022"), an NER dataset on Twitter with 7 entity labels. Each instance of TweetNER7 comes with
a timestamp which distributes from September 2019 to August 2021.
- Entity Types: `corperation`, `creative_work`, `event`, `group`, `location`, `product`, `person` 

### Preprocessing
We pre-process tweets before the annotation to normalize some artifacts, converting URLs into a special token `{{URL}}` and non-verified usernames into `{{USERNAME}}`.
For verified usernames, we replace its display name with symbols `{@}`.
For example, a tweet

```
Get the all-analog Classic Vinyl Edition
of "Takin' Off" Album from @herbiehancock
via @bluenoterecords link below: 
http://bluenote.lnk.to/AlbumOfTheWeek
```

is transformed into the following text.
```
Get the all-analog Classic Vinyl Edition
of "Takin' Off" Album from {@Herbie Hancock@}
via {{USERNAME}} link below: {{URL}}
```

A simple function to format tweet follows below.

```python
import re
from urlextract import URLExtract
extractor = URLExtract()

def format_tweet(tweet):
    # mask web urls
    urls = extractor.find_urls(tweet)
    for url in urls:
        tweet = tweet.replace(url, "{{URL}}")
    # format twitter account
    tweet = re.sub(r"\b(\s*)(@[\S]+)\b", r'\1{\2@}', tweet)
    return tweet

target = """Get the all-analog Classic Vinyl Edition of "Takin' Off" Album from @herbiehancock via @bluenoterecords link below: http://bluenote.lnk.to/AlbumOfTheWeek"""
target_format = format_tweet(target)
print(target_format)
'Get the all-analog Classic Vinyl Edition of "Takin\' Off" Album from {@herbiehancock@} via {@bluenoterecords@} link below: {{URL}}'
```


We ask annotators to ignore those special tokens but label the verified users' mentions.


### Data Split

| split             | number of instances | description |
|:------------------|------:|------:|
| train_2020        |  4616 | training dataset from September 2019 to August 2020 |
| train_2021        |  2495 | training dataset from September 2020 to August 2021 |
| train_all         |  7111 | combined training dataset of `train_2020` and `train_2021` |
| validation_2020   |   576 | validation dataset from September 2019 to August 2020 |
| validation_2021   |   310 | validation dataset from September 2020 to August 2021 | 
| validation_all    |   886 | combined validation dataset of `validation_2020` and `validation_2021` |
| test_2020         |   576 | test dataset from September 2019 to August 2020 |
| test_2021         |  2807 | test dataset from September 2020 to August 2021 |
| test_all          |  3383 | combined test dataset of `test_2020` and `test_2021` |
| train_random      |  4616 | randomly sampled training dataset with the same size as `train_2020` from `train_all` |
| validation_random |   576 | randomly sampled training dataset with the same size as `validation_2020` from `validation_all` |
| extra_2020        | 87880 | extra tweet without annotations from September 2019 to August 2020 |
| extra_2021        | 93594 | extra tweet without annotations from September 2020 to August 2021 |


### Reproduce Experimental Result

To reproduce the experimental result on our AACL paper, please see the repository 
[https://github.com/asahi417/tner/tree/master/examples/tweetner7_paper](https://github.com/asahi417/tner/tree/master/examples/tweetner7_paper).

## Dataset Structure

### Data Instances
An example of `train` looks as follows.

```
{
    'tokens': ['Morning', '5km', 'run', 'with', '{{USERNAME}}', 'for', 'breast', 'cancer', 'awareness', '#', 'pinkoctober', '#', 'breastcancerawareness', '#', 'zalorafit', '#', 'zalorafitxbnwrc', '@', 'The', 'Central', 'Park', ',', 'Desa', 'Parkcity', '{{URL}}'],
    'tags': [14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 2, 14, 2, 14, 14, 14, 14, 14, 14, 4, 11, 11, 11, 11, 14],
    'id': '1183344337016381440',
    'date': '2019-10-13'
}
```

### Label ID
The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/tweetner7/raw/main/dataset/label.json).
```python
{
    "B-corporation": 0,
    "B-creative_work": 1,
    "B-event": 2,
    "B-group": 3,
    "B-location": 4,
    "B-person": 5,
    "B-product": 6,
    "I-corporation": 7,
    "I-creative_work": 8,
    "I-event": 9,
    "I-group": 10,
    "I-location": 11,
    "I-person": 12,
    "I-product": 13,
    "O": 14
}
```


### Citation Information

```
@inproceedings{ushio-etal-2022-tweet,
    title = "{N}amed {E}ntity {R}ecognition in {T}witter: {A} {D}ataset and {A}nalysis on {S}hort-{T}erm {T}emporal {S}hifts",
    author = "Ushio, Asahi  and
        Neves, Leonardo  and
        Silva, Vitor  and
        Barbieri, Francesco. and
        Camacho-Collados, Jose",
    booktitle = "The 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing",
    month = nov,
    year = "2022",
    address = "Online",
    publisher = "Association for Computational Linguistics",
}
```