
# Dataset Card for SentiNews

## Dataset Description

- **Homepage:** https://github.com/19Joey85/Sentiment-annotated-news-corpus-and-sentiment-lexicon-in-Slovene  
- **Paper:** Bučar, J., Žnidaršič, M. & Povh, J. Annotated news corpora and a lexicon for sentiment analysis in Slovene. Lang Resources & Evaluation 52, 895–919 (2018). https://doi.org/10.1007/s10579-018-9413-3

### Dataset Summary

SentiNews is a Slovenian sentiment classification dataset, consisting of news articles manually annotated with their sentiment by between two and six annotators.
It is annotated at three granularities: 
- document-level (config `document_level`, 10 427 documents), 
- paragraph-level (config `paragraph_level`, 89 999 paragraphs), and 
- sentence-level (config `sentence_level`, 168 899 sentences).

### Supported Tasks and Leaderboards

Sentiment classification, three classes (negative, neutral, positive).

### Languages

Slovenian.

## Dataset Structure

### Data Instances

A sample instance from the sentence-level config:
```
{
  'nid': 2, 
  'content': 'Vilo Prešeren je na dražbi ministrstva za obrambo kupilo nepremičninsko podjetje Condor Real s sedežem v Lescah.', 
  'sentiment': 'neutral', 
  'pid': 1, 
  'sid': 1
}
```

### Data Fields

The data fields are similar among all three configs, with the only difference being the IDs.

- `nid`: a uint16 containing a unique ID of the news article (document). 
- `content`: a string containing the body of the news article 
- `sentiment`: the sentiment of the instance
- `pid`: a uint8 containing the consecutive number of the paragraph inside the current news article, **not unique** (present in the configs `paragraph_level` and `sentence_level`)
- `sid`: a uint8 containing the consecutive number of the sentence inside the current paragraph, **not unique** (present in the config `sentence_level`)

## Additional Information

### Dataset Curators

Jože Bučar, Martin Žnidaršič, Janez Povh.

### Licensing Information

CC BY-SA 4.0

### Citation Information

```
@article{buvcar2018annotated, 
  title={Annotated news corpora and a lexicon for sentiment analysis in Slovene}, 
  author={Bu{\v{c}}ar, Jo{\v{z}}e and {\v{Z}}nidar{\v{s}}i{\v{c}}, Martin and Povh, Janez}, 
  journal={Language Resources and Evaluation}, 
  volume={52}, 
  number={3}, 
  pages={895--919}, 
  year={2018}, 
  publisher={Springer}
}
```

### Contributions

Thanks to [@matejklemen](https://github.com/matejklemen) for adding this dataset.

task_categories:text-classification task_ids:sentiment-classification annotations_creators:crowdsourced language_creators:found multilinguality:monolingual source_datasets:original language:sl license:cc-by-sa-4.0 slovenian sentiment news articles region:us
{"annotations_creators": ["crowdsourced"], "language_creators": ["found"], "language": ["sl"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": [], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "pretty_name": "SentiNews", "tags": ["slovenian sentiment", "news articles"]}
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #source_datasets-original #language-Slovenian #license-cc-by-sa-4.0 #slovenian sentiment #news articles #region-us 


# Dataset Card for SentiNews

## Dataset Description

- Homepage: URL  
- Paper: Bučar, J., Žnidaršič, M. & Povh, J. Annotated news corpora and a lexicon for sentiment analysis in Slovene. Lang Resources & Evaluation 52, 895–919 (2018). URL

### Dataset Summary

SentiNews is a Slovenian sentiment classification dataset, consisting of news articles manually annotated with their sentiment by between two and six annotators.
It is annotated at three granularities: 
- document-level (config 'document_level', 10 427 documents), 
- paragraph-level (config 'paragraph_level', 89 999 paragraphs), and 
- sentence-level (config 'sentence_level', 168 899 sentences).

### Supported Tasks and Leaderboards

Sentiment classification, three classes (negative, neutral, positive).

### Languages

Slovenian.

## Dataset Structure

### Data Instances

A sample instance from the sentence-level config:


### Data Fields

The data fields are similar among all three configs, with the only difference being the IDs.

- 'nid': a uint16 containing a unique ID of the news article (document). 
- 'content': a string containing the body of the news article 
- 'sentiment': the sentiment of the instance
- 'pid': a uint8 containing the consecutive number of the paragraph inside the current news article, not unique (present in the configs 'paragraph_level' and 'sentence_level')
- 'sid': a uint8 containing the consecutive number of the sentence inside the current paragraph, not unique (present in the config 'sentence_level')

## Additional Information

### Dataset Curators

Jože Bučar, Martin Žnidaršič, Janez Povh.

### Licensing Information

CC BY-SA 4.0





### Contributions

Thanks to @matejklemen for adding this dataset.

# Dataset Card for SentiNews ## Dataset Description

- Homepage: URL  
- Paper: Bučar, J., Žnidaršič, M. & Povh, J. Annotated news corpora and a lexicon for sentiment analysis in Slovene. Lang Resources & Evaluation 52, 895–919 (2018). URL ### Dataset Summary

SentiNews is a Slovenian sentiment classification dataset, consisting of news articles manually annotated with their sentiment by between two and six annotators.
It is annotated at three granularities: 
- document-level (config 'document_level', 10 427 documents), 
- paragraph-level (config 'paragraph_level', 89 999 paragraphs), and 
- sentence-level (config 'sentence_level', 168 899 sentences). ### Supported Tasks and Leaderboards

Sentiment classification, three classes (negative, neutral, positive). ### Languages

Slovenian. ## Dataset Structure ### Data Instances

A sample instance from the sentence-level config: ### Data Fields

The data fields are similar among all three configs, with the only difference being the IDs.

- 'nid': a uint16 containing a unique ID of the news article (document). 
- 'content': a string containing the body of the news article 
- 'sentiment': the sentiment of the instance
- 'pid': a uint8 containing the consecutive number of the paragraph inside the current news article, not unique (present in the configs 'paragraph_level' and 'sentence_level')
- 'sid': a uint8 containing the consecutive number of the sentence inside the current paragraph, not unique (present in the config 'sentence_level') ## Additional Information ### Dataset Curators

Jože Bučar, Martin Žnidaršič, Janez Povh. ### Licensing Information

CC BY-SA 4.0 ### Contributions

Thanks to @matejklemen for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #source_datasets-original #language-Slovenian #license-cc-by-sa-4.0 #slovenian sentiment #news articles #region-us 
 # Dataset Card for SentiNews ## Dataset Description

- Homepage: URL  
- Paper: Bučar, J., Žnidaršič, M. & Povh, J. Annotated news corpora and a lexicon for sentiment analysis in Slovene. Lang Resources & Evaluation 52, 895–919 (2018). URL ### Dataset Summary

SentiNews is a Slovenian sentiment classification dataset, consisting of news articles manually annotated with their sentiment by between two and six annotators.
It is annotated at three granularities: 
- document-level (config 'document_level', 10 427 documents), 
- paragraph-level (config 'paragraph_level', 89 999 paragraphs), and 
- sentence-level (config 'sentence_level', 168 899 sentences). ### Supported Tasks and Leaderboards

Sentiment classification, three classes (negative, neutral, positive). ### Languages

Slovenian. ## Dataset Structure ### Data Instances

A sample instance from the sentence-level config: ### Data Fields

The data fields are similar among all three configs, with the only difference being the IDs.

- 'nid': a uint16 containing a unique ID of the news article (document). 
- 'content': a string containing the body of the news article 
- 'sentiment': the sentiment of the instance
- 'pid': a uint8 containing the consecutive number of the paragraph inside the current news article, not unique (present in the configs 'paragraph_level' and 'sentence_level')
- 'sid': a uint8 containing the consecutive number of the sentence inside the current paragraph, not unique (present in the config 'sentence_level') ## Additional Information ### Dataset Curators

Jože Bučar, Martin Žnidaršič, Janez Povh. ### Licensing Information

CC BY-SA 4.0 ### Contributions

Thanks to @matejklemen for adding this dataset.
passage: TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #source_datasets-original #language-Slovenian #license-cc-by-sa-4.0 #slovenian sentiment #news articles #region-us 
# Dataset Card for SentiNews## Dataset Description

- Homepage: URL  
- Paper: Bučar, J., Žnidaršič, M. & Povh, J. Annotated news corpora and a lexicon for sentiment analysis in Slovene. Lang Resources & Evaluation 52, 895–919 (2018). URL### Dataset Summary

SentiNews is a Slovenian sentiment classification dataset, consisting of news articles manually annotated with their sentiment by between two and six annotators.
It is annotated at three granularities: 
- document-level (config 'document_level', 10 427 documents), 
- paragraph-level (config 'paragraph_level', 89 999 paragraphs), and 
- sentence-level (config 'sentence_level', 168 899 sentences).### Supported Tasks and Leaderboards

Sentiment classification, three classes (negative, neutral, positive).### Languages

Slovenian.## Dataset Structure### Data Instances

A sample instance from the sentence-level config:### Data Fields

The data fields are similar among all three configs, with the only difference being the IDs.

- 'nid': a uint16 containing a unique ID of the news article (document). 
- 'content': a string containing the body of the news article 
- 'sentiment': the sentiment of the instance
- 'pid': a uint8 containing the consecutive number of the paragraph inside the current news article, not unique (present in the configs 'paragraph_level' and 'sentence_level')
- 'sid': a uint8 containing the consecutive number of the sentence inside the current paragraph, not unique (present in the config 'sentence_level')## Additional Information### Dataset Curators

Jože Bučar, Martin Žnidaršič, Janez Povh.