
# Dataset Card for news-data

## Table of Contents
- [Table of Contents](#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)
 
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)

  - [Dataset Curators](#dataset-curators)
 

### Dataset Summary

The News Dataset is an English-language dataset containing just over 4k unique news articles scrapped from AriseTv- One of the most popular news television in Nigeria. 
### Supported Tasks and Leaderboards

It supports news article classification into different categories.

### Languages

English

## Dataset Structure

### Data Instances

'''
{'Title': 'Nigeria: APC Yet to Zone Party Positions Ahead of Convention'
 'Excerpt': 'The leadership of the All Progressives Congress (APC), has denied reports that it had zoned some party positions ahead of'
 'Category': 'politics'
 'labels': 2}
 '''

### Data Fields
* Title: a string containing the title of a news title as shown
* Excerpt: a string containing a short extract from the body of the news
* Category: a string that tells the category of an example (string label)
* labels: integer telling the class of an example (label)

### Data Splits

| Dataset Split      | Number of instances in split |
| -----------        | ----------- |
| Train              | 4,594      |
| Paragraph          | 811      |

## Dataset Creation

### Source Data

#### Initial Data Collection and Normalization

The code for the dataset creation at *https://github.com/chimaobi-okite/NLP-Projects-Competitions/blob/main/NewsCategorization/Data/NewsDataScraping.ipynb*. The examples were scrapped from
<https://www.arise.tv/>


### Annotations

#### Annotation process

The annotation is based on the news category in the [arisetv](https://www.arise.tv) website

#### Who are the annotators?

Journalists at arisetv

## Considerations for Using the Data

### Social Impact of Dataset

The purpose of this dataset is to help develop models that can classify news articles into categories.

This task is useful for efficiently presenting information given a large quantity of text. It should be made clear that any summarizations produced by models trained on this dataset are reflective of the language used in the articles, but are in fact automatically generated.

### Discussion of Biases
This data is biased towards news happenings in Nigeria but the model built using it can as well classify news from other parts of the world 
with a slight degradation in performance.


### Dataset Curators

The dataset is created by people at arise but was scrapped by [@github-chimaobi-okite](https://github.com/chimaobi-okite/)

task_categories:text-classification task_ids:topic-classification task_ids:multi-class-classification annotations_creators:other language_creators:found multilinguality:monolingual size_categories:1K<n<10K source_datasets:original language:en license:afl-3.0 region:us
{"annotations_creators": ["other"], "language_creators": ["found"], "language": ["en"], "license": ["afl-3.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["topic-classification", "multi-class-classification"], "pretty_name": "News Dataset", "tags": []}
TAGS
#task_categories-text-classification #task_ids-topic-classification #task_ids-multi-class-classification #annotations_creators-other #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-afl-3.0 #region-us 

Dataset Card for news-data
==========================


Table of Contents
-----------------


* 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
* Considerations for Using the Data


	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Dataset Curators


### Dataset Summary


The News Dataset is an English-language dataset containing just over 4k unique news articles scrapped from AriseTv- One of the most popular news television in Nigeria.


### Supported Tasks and Leaderboards


It supports news article classification into different categories.


### Languages


English


Dataset Structure
-----------------


### Data Instances


'''
{'Title': 'Nigeria: APC Yet to Zone Party Positions Ahead of Convention'
'Excerpt': 'The leadership of the All Progressives Congress (APC), has denied reports that it had zoned some party positions ahead of'
'Category': 'politics'
'labels': 2}
'''


### Data Fields


* Title: a string containing the title of a news title as shown
* Excerpt: a string containing a short extract from the body of the news
* Category: a string that tells the category of an example (string label)
* labels: integer telling the class of an example (label)


### Data Splits



Dataset Creation
----------------


### Source Data


#### Initial Data Collection and Normalization


The code for the dataset creation at \*URL The examples were scrapped from
<URL


### Annotations


#### Annotation process


The annotation is based on the news category in the arisetv website


#### Who are the annotators?


Journalists at arisetv


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


The purpose of this dataset is to help develop models that can classify news articles into categories.


This task is useful for efficiently presenting information given a large quantity of text. It should be made clear that any summarizations produced by models trained on this dataset are reflective of the language used in the articles, but are in fact automatically generated.


### Discussion of Biases


This data is biased towards news happenings in Nigeria but the model built using it can as well classify news from other parts of the world
with a slight degradation in performance.


### Dataset Curators


The dataset is created by people at arise but was scrapped by @github-chimaobi-okite



### Dataset Summary


The News Dataset is an English-language dataset containing just over 4k unique news articles scrapped from AriseTv- One of the most popular news television in Nigeria. ### Supported Tasks and Leaderboards


It supports news article classification into different categories. ### Languages


English


Dataset Structure
----------------- ### Data Instances


'''
{'Title': 'Nigeria: APC Yet to Zone Party Positions Ahead of Convention'
'Excerpt': 'The leadership of the All Progressives Congress (APC), has denied reports that it had zoned some party positions ahead of'
'Category': 'politics'
'labels': 2}
''' ### Data Fields


* Title: a string containing the title of a news title as shown
* Excerpt: a string containing a short extract from the body of the news
* Category: a string that tells the category of an example (string label)
* labels: integer telling the class of an example (label) ### Data Splits



Dataset Creation
---------------- ### Source Data #### Initial Data Collection and Normalization


The code for the dataset creation at \*URL The examples were scrapped from
<URL ### Annotations #### Annotation process


The annotation is based on the news category in the arisetv website #### Who are the annotators?


Journalists at arisetv


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset


The purpose of this dataset is to help develop models that can classify news articles into categories.


This task is useful for efficiently presenting information given a large quantity of text. It should be made clear that any summarizations produced by models trained on this dataset are reflective of the language used in the articles, but are in fact automatically generated. ### Discussion of Biases


This data is biased towards news happenings in Nigeria but the model built using it can as well classify news from other parts of the world
with a slight degradation in performance. ### Dataset Curators


The dataset is created by people at arise but was scrapped by @github-chimaobi-okite
TAGS
#task_categories-text-classification #task_ids-topic-classification #task_ids-multi-class-classification #annotations_creators-other #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-afl-3.0 #region-us 
 ### Dataset Summary


The News Dataset is an English-language dataset containing just over 4k unique news articles scrapped from AriseTv- One of the most popular news television in Nigeria. ### Supported Tasks and Leaderboards


It supports news article classification into different categories. ### Languages


English


Dataset Structure
----------------- ### Data Instances


'''
{'Title': 'Nigeria: APC Yet to Zone Party Positions Ahead of Convention'
'Excerpt': 'The leadership of the All Progressives Congress (APC), has denied reports that it had zoned some party positions ahead of'
'Category': 'politics'
'labels': 2}
''' ### Data Fields


* Title: a string containing the title of a news title as shown
* Excerpt: a string containing a short extract from the body of the news
* Category: a string that tells the category of an example (string label)
* labels: integer telling the class of an example (label) ### Data Splits



Dataset Creation
---------------- ### Source Data #### Initial Data Collection and Normalization


The code for the dataset creation at \*URL The examples were scrapped from
<URL ### Annotations #### Annotation process


The annotation is based on the news category in the arisetv website #### Who are the annotators?


Journalists at arisetv


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset


The purpose of this dataset is to help develop models that can classify news articles into categories.


This task is useful for efficiently presenting information given a large quantity of text. It should be made clear that any summarizations produced by models trained on this dataset are reflective of the language used in the articles, but are in fact automatically generated. ### Discussion of Biases


This data is biased towards news happenings in Nigeria but the model built using it can as well classify news from other parts of the world
with a slight degradation in performance. ### Dataset Curators


The dataset is created by people at arise but was scrapped by @github-chimaobi-okite