---
language:
- 'no'
pretty_name: NoReC
size_categories:
- 10K<n<100K
license: cc
---
# NoReC: The Norwegian Review Corpus
This repository distributes the Norwegian Review Corpus (NoReC), created for the purpose of training and evaluating models for document-level sentiment analysis. 
More than 43,000 full-text reviews have been collected from major Norwegian news sources and cover a range of different domains, including literature, movies, video games, restaurants, music and theater, in addition to product reviews across a range of categories. Each review is labeled with a manually assigned score of 1–6, as provided by the rating of the original author. The accompanying [paper](http://www.lrec-conf.org/proceedings/lrec2018/pdf/851.pdf) by Velldal et al. at LREC 2018 describes the (initial release of the) data in more detail. 

id, split, rating, category, day, month, year, excerpt, language, source, authors, title, url, text




- **Curated by:** [More Information Needed]
- **Funding:** 
NoReC was created as part of the [SANT](https://www.mn.uio.no/ifi/english/research/projects/sant/) project (Sentiment Analysis for Norwegian Text),
a collaboration between the Language Technology Group (LTG) at the Department of Informatics at the University of Oslo, the Norwegian Broadcasting Corporation (NRK), Schibsted Media Group and Aller Media.

- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** Norwegian Bokmål (nb) and Norwegian Nynorsk (nn)
- **License:** 
The data is distributed under a Creative Commons Attribution-NonCommercial licence (CC BY-NC 4.0), access the full license text here: https://creativecommons.org/licenses/by-nc/4.0/
The licence is motivated by the need to block the possibility of third parties redistributing the orignal reviews for commercial purposes. 
Note that **machine learned models**, extracted **lexicons**, **embeddings**, and similar resources that are created on the basis of NoReC are not considered to contain the original data and so **can be freely used also for commercial purposes** despite the non-commercial condition. 

### Dataset Sources [optional]
This verion of the corpus comprises 43,436 review texts extracted from eight different news sources: Dagbladet, VG, Aftenposten, Bergens Tidende, Fædrelandsvennen, Stavanger Aftenblad, DinSide.no and P3.no.
<!-- Provide the basic links for the dataset. -->

- **Repository:** https://github.com/ltgoslo/norec.git
- **Paper [optional]:**  The accompanying paper by Velldal et al. at LREC 2018 describes the (initial release of the) data in more detail.


## Uses

The dataset is intended for document-level sentiment analysis, to learn to predict the rating from the text. The field "category" can be considered til "domain" of each text. By filtering in and out category values, one may inspect cross-domain performance of a model.


## Source Data
This _2nd release, v.2.1_ of the corpus comprises 43,436 review texts extracted from eight different news sources: Dagbladet, VG, Aftenposten, Bergens Tidende, Fædrelandsvennen, Stavanger Aftenblad, DinSide.no and P3.no. 
In terms of publishing date the reviews mainly cover the time span 2003–2019, although it also includes a handful of reviews dating back as far as 1998.


# Some statistics
## Distribution over year and publication source
All splits combined

|   year |   ap |   bt |   db        |   dinside |   fvn |   p3 |   sa |   vg |   Total |
|-------:|-----:|-----:|------------:|----------:|------:|-----:|-----:|-----:|--------:|
|  2003* |    0 |    4 |           0 |       143 |     0 |   25 |    0 |  286 |     458 |
|   2004 |    0 |   44 |           0 |       142 |     0 |   12 |   19 |  984 |    1201 |
|   2005 |    0 |    0 |           0 |       179 |     0 |    6 |  224 |  909 |    1318 |
|   2006 |    0 |    0 |           0 |       240 |     0 |   11 |  294 |  778 |    1323 |
|   2007 |    0 |    0 |           0 |       139 |     0 |  127 |  400 |  725 |    1391 |
|   2008 |    0 |    0 |           0 |       119 |     0 |  216 |  369 |  739 |    1443 |
|   2009 |    0 |   52 |         377 |       163 |    27 |  428 |  259 |  815 |    2121 |
|   2010 |    0 |  100 |         642 |       260 |   156 |  571 |  309 |  769 |    2807 |
|   2011 |    1 |   51 |         592 |       284 |   146 |  652 |  362 |  900 |    2988 |
|   2012 |    2 |  150 |         613 |       257 |   332 |  611 |  561 |  763 |    3289 |
|   2013 |    4 |  160 |         527 |       216 |   213 |  619 |  433 | 1058 |    3230 |
|   2014 |   39 |  291 |         501 |       236 |   357 |  546 |  387 | 1191 |    3548 |
|   2015 |  249 |  235 |         728 |       245 |   456 |  499 |  620 |  849 |    3881 |
|   2016 |  309 |  340 |         809 |       177 |   321 |  439 |  682 |  715 |    3792 |
|   2017 |  649 |  491 |         921 |       248 |   692 |  567 |  822 |  687 |    5077 |
|   2018 |  605 |  470 |         885 |       194 |   466 |  339 |  860 |  492 |    4311 |
|   2019 |  260 |  167 |          95 |        30 |   160 |   36 |  346 |  165 |    1259 |

`2003*`: Including the 31 documents 1998-2002

## Distribution over split and rating 

| split   |   1 |    2 |    3 |     4 |     5 |    6 |   Total |
|:--------|----:|-----:|-----:|------:|------:|-----:|--------:|
| dev     |  51 |  225 |  707 |  1409 |  1678 |  278 |    4348 |
| test    |  27 |  242 |  706 |  1385 |  1714 |  266 |    4340 |
| train   | 379 | 2287 | 6004 | 11304 | 12614 | 2161 |   34749 |

## Distribution over split and category
| split   |   games |   literature |   misc |   music |   products |   restaurants |   screen |   sports |   stage |   Total |
|:--------|--------:|-------------:|-------:|--------:|-----------:|--------------:|---------:|---------:|--------:|--------:|
| dev     |     179 |          539 |     28 |    1445 |        347 |            94 |     1569 |       15 |     132 |    4348 |
| test    |     180 |          547 |     24 |    1444 |        345 |            98 |     1579 |       16 |     107 |    4340 |
| train   |    1453 |         4337 |    156 |   11777 |       2771 |           745 |    12536 |      118 |     856 |   34749 |


#### Data Collection and Processing

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[More Information Needed]

#### Who are the source data producers?

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### Annotations [optional]

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#### Annotation process

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#### Who are the annotators?

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#### Personal and Sensitive Information

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## Bias, Risks, and Limitations

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### Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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