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metadata
language:
  - 'no'
license: cc
size_categories:
  - 10K<n<100K
pretty_name: NoReC
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
dataset_info:
  language:
    - 'no'
  license: cc
  size_categories:
    - 10K<n<100K
  pretty_name: NoReC
  configs:
    - config_name: default
      data_files:
        - split: train
          path: data/train-*
        - split: validation
          path: data/validation-*
        - split: test
          path: data/test-*
  dataset_info:
    features:
      - name: id
        dtype: string
      - name: split
        dtype: string
      - name: rating
        dtype: int64
      - name: category
        dtype: string
      - name: day
        dtype: int64
      - name: month
        dtype: int64
      - name: year
        dtype: int64
      - name: excerpt
        dtype: string
      - name: language
        dtype: string
      - name: source
        dtype: string
      - name: authors
        dtype: string
      - name: title
        dtype: string
      - name: url
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 94334212
        num_examples: 34749
      - name: validation
        num_bytes: 13597517
        num_examples: 4348
      - name: test
        num_bytes: 13787751
        num_examples: 4340
    download_size: 77286913
    dataset_size: 121719480
  homepage: https://github.com/ltgoslo/norec
  citation: |-
    @InProceedings{VelOvrBer18,
      author = {Erik Velldal and Lilja {\O}vrelid and 
                Eivind Alexander Bergem and  Cathrine Stadsnes and 
                Samia Touileb and Fredrik J{\o}rgensen},
      title = {{NoReC}: The {N}orwegian {R}eview {C}orpus},
      booktitle = {Proceedings of the 11th edition of the 
                   Language Resources and Evaluation Conference},
      year = {2018},
      address = {Miyazaki, Japan},
      pages = {4186--4191}
    }
    }
task_categories:
  - text-classification

NoReC: The Norwegian Review Corpus

This is the official repository for the Norwegian Review Corpus (NoReC, ver. 2.1), 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 by Velldal et al. at LREC 2018 describes the initial (ver. 1) release of the data in more detail.

Dataset details

  • The columns are: id, split, rating, category, day, month, year, excerpt, language, source, authors, title, url, text where basic usage has text as the input and rating as the output.
  • Curated by: NoReC was created as part of the SANT project (Sentiment Analysis for Norwegian Text), coordinated by the Language Technology Group (LTG) at the University of Oslo, in collaboration with the Norwegian Broadcasting Corporation (NRK), Schibsted Media Group and Aller Media.
  • Funded by: The SANT project is funded by the Research Council of Norway (NFR grant number 270908).
  • Shared by: The SANT project (Sentiment Analysis for Norwegian Text) at the Language Technology Group (LTG) at the University of Oslo
  • 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 This version of the corpus (v.2.1) comprises 43,436 review texts extracted from eight different news sources: Dagbladet, VG, Aftenposten, Bergens Tidende, Fædrelandsvennen, Stavanger Aftenblad, DinSide.no and P3.no.
  • Repository: https://github.com/ltgoslo/norec
  • Paper : 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 the "domain" of each text. By filtering in and out category values, one may inspect cross-domain performance of a model. The other fields contain metadata preserved from the original version of the dataset, and may be used for further filtering and analyses.

Source Data

This 2nd release, v.2.1 of the corpus comprises 43,436 review texts extracted from eight different news sources: Dagbladet (db), VG (vg), Aftenposten (ap), Bergens Tidende (bt), Fædrelandsvennen (fvn), Stavanger Aftenblad (sa), DinSide.no (dinside) and P3.no (p3).

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

Citation

@InProceedings{VelOvrBer18,
  author = {Erik Velldal and Lilja {\O}vrelid and Eivind Alexander Bergem and  Cathrine Stadsnes and Samia Touileb and Fredrik J{\o}rgensen},
  title = {{NoReC}: The {N}orwegian {R}eview {C}orpus},
  booktitle = {Proceedings of the 11th edition of the 
               Language Resources and Evaluation Conference},
  year = {2018},
  address = {Miyazaki, Japan},
  pages = {4186--4191}
}

Dataset Card Authors

Vladislav Mikhailov and Erik Velldal

Dataset Card Contact

[email protected] and [email protected]