
# Dataset Card for [Dataset Name]

## 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://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection
- **Repository:**
- **Paper:** Almeida, T.A., Gomez Hidalgo, J.M., Yamakami, A. Contributions to the study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (ACM DOCENG'11), Mountain View, CA, USA, 2011.
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.
It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

English

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

- sms: the sms message
- label: indicating if the sms message is ham or spam, ham means it is not spam

### Data Splits

[More Information Needed]

## 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

@inproceedings{Almeida2011SpamFiltering,
  title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},
  author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},
  year={2011},
  booktitle = "Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)",
}

### Contributions

Thanks to [@czabo](https://github.com/czabo) for adding this dataset.
task_categories:text-classification task_ids:intent-classification annotations_creators:crowdsourced annotations_creators:found language_creators:crowdsourced language_creators:found multilinguality:monolingual size_categories:1K<n<10K source_datasets:extended|other-nus-sms-corpus language:en license:unknown region:us
{"annotations_creators": ["crowdsourced", "found"], "language_creators": ["crowdsourced", "found"], "language": ["en"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["extended|other-nus-sms-corpus"], "task_categories": ["text-classification"], "task_ids": ["intent-classification"], "paperswithcode_id": "sms-spam-collection-data-set", "pretty_name": "SMS Spam Collection Data Set", "dataset_info": {"features": [{"name": "sms", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "ham", "1": "spam"}}}}], "config_name": "plain_text", "splits": [{"name": "train", "num_bytes": 521756, "num_examples": 5574}], "download_size": 203415, "dataset_size": 521756}, "train-eval-index": [{"config": "plain_text", "task": "text-classification", "task_id": "binary_classification", "splits": {"train_split": "train"}, "col_mapping": {"sms": "text", "label": "target"}, "metrics": [{"type": "accuracy", "name": "Accuracy"}, {"type": "f1", "name": "F1 macro", "args": {"average": "macro"}}, {"type": "f1", "name": "F1 micro", "args": {"average": "micro"}}, {"type": "f1", "name": "F1 weighted", "args": {"average": "weighted"}}, {"type": "precision", "name": "Precision macro", "args": {"average": "macro"}}, {"type": "precision", "name": "Precision micro", "args": {"average": "micro"}}, {"type": "precision", "name": "Precision weighted", "args": {"average": "weighted"}}, {"type": "recall", "name": "Recall macro", "args": {"average": "macro"}}, {"type": "recall", "name": "Recall micro", "args": {"average": "micro"}}, {"type": "recall", "name": "Recall weighted", "args": {"average": "weighted"}}]}]}
TAGS
#task_categories-text-classification #task_ids-intent-classification #annotations_creators-crowdsourced #annotations_creators-found #language_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-extended|other-nus-sms-corpus #language-English #license-unknown #region-us 


# Dataset Card for [Dataset Name]

## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions

## Dataset Description

- Homepage: URL
- Repository:
- Paper: Almeida, T.A., Gomez Hidalgo, J.M., Yamakami, A. Contributions to the study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (ACM DOCENG'11), Mountain View, CA, USA, 2011.
- Leaderboard:
- Point of Contact:

### Dataset Summary

The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.
It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.

### Supported Tasks and Leaderboards



### Languages

English

## Dataset Structure

### Data Instances



### Data Fields

- sms: the sms message
- label: indicating if the sms message is ham or spam, ham means it is not spam

### Data Splits



## Dataset Creation

### Curation Rationale



### Source Data

#### Initial Data Collection and Normalization



#### Who are the source language producers?



### Annotations

#### Annotation process



#### Who are the annotators?



### Personal and Sensitive Information



## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators



### Licensing Information





@inproceedings{Almeida2011SpamFiltering,
  title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},
  author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},
  year={2011},
  booktitle = "Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)",
}

### Contributions

Thanks to @czabo for adding this dataset.
# Dataset Card for [Dataset Name] ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Homepage: URL
- Repository:
- Paper: Almeida, T.A., Gomez Hidalgo, J.M., Yamakami, A. Contributions to the study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (ACM DOCENG'11), Mountain View, CA, USA, 2011.
- Leaderboard:
- Point of Contact: ### Dataset Summary

The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.
It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam. ### Supported Tasks and Leaderboards ### Languages

English ## Dataset Structure ### Data Instances ### Data Fields

- sms: the sms message
- label: indicating if the sms message is ham or spam, ham means it is not spam ### Data Splits ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information





@inproceedings{Almeida2011SpamFiltering,
  title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},
  author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},
  year={2011},
  booktitle = "Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)",
} ### Contributions

Thanks to @czabo for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-intent-classification #annotations_creators-crowdsourced #annotations_creators-found #language_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-extended|other-nus-sms-corpus #language-English #license-unknown #region-us 
 # Dataset Card for [Dataset Name] ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Homepage: URL
- Repository:
- Paper: Almeida, T.A., Gomez Hidalgo, J.M., Yamakami, A. Contributions to the study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (ACM DOCENG'11), Mountain View, CA, USA, 2011.
- Leaderboard:
- Point of Contact: ### Dataset Summary

The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.
It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam. ### Supported Tasks and Leaderboards ### Languages

English ## Dataset Structure ### Data Instances ### Data Fields

- sms: the sms message
- label: indicating if the sms message is ham or spam, ham means it is not spam ### Data Splits ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information





@inproceedings{Almeida2011SpamFiltering,
  title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},
  author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},
  year={2011},
  booktitle = "Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)",
} ### Contributions

Thanks to @czabo for adding this dataset.
passage: TAGS
#task_categories-text-classification #task_ids-intent-classification #annotations_creators-crowdsourced #annotations_creators-found #language_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-extended|other-nus-sms-corpus #language-English #license-unknown #region-us 
# Dataset Card for [Dataset Name]## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions## Dataset Description

- Homepage: URL
- Repository:
- Paper: Almeida, T.A., Gomez Hidalgo, J.M., Yamakami, A. Contributions to the study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (ACM DOCENG'11), Mountain View, CA, USA, 2011.
- Leaderboard:
- Point of Contact:### Dataset Summary

The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.
It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.### Supported Tasks and Leaderboards### Languages

English## Dataset Structure### Data Instances### Data Fields

- sms: the sms message
- label: indicating if the sms message is ham or spam, ham means it is not spam### Data Splits## Dataset Creation### Curation Rationale### Source Data#### Initial Data Collection and Normalization