| dc.creator | Bizzoni, Yuri |
| dc.creator | Feldkamp, Pascale |
| dc.creator | Nielbo, Kristoffer |
| dc.creator | Lassen, Ida-Marie |
| dc.creator | Thomsen, Mads |
| dc.date.accessioned | 2024-09-02T08:53:01Z |
| dc.date.available | 2024-09-02T08:53:01Z |
| dc.date.issued | 2024-05-01 |
| dc.identifier.uri | http://hdl.handle.net/20.500.12115/56 |
| dc.description | A dataset designed to study literary fiction's quality as a multidimensional construct with several different proxies for reception and assessment (e.g. Goodreads' scores, libraries' holdings, selection for long-listed awards, presence in canonical anthologies etc.). The dataset contains metadata and tens of linguistic features for more than 9000 contemporary novels. Ideal for study of literary quality and reception. An extensive description of the measures annotated in the corpus can be found at GitHub: https://github.com/centre-for-humanities-computing/chicago_corpus/blob/main/data/corpus_description.md |
| dc.language.iso | eng |
| dc.publisher | University Århus |
| dc.relation.isreferencedby | https://aclanthology.org/2024.lrec-main.71/ |
| dc.rights | Creative Commons - Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.rights.label | PUB |
| dc.source.uri | https://centre-for-humanities-computing.github.io/fabula-net/ |
| dc.subject | literature |
| dc.subject | sentiment analysis |
| dc.subject | literary quality |
| dc.subject | computational literary studies |
| dc.subject | computational linguistics |
| dc.title | FabulaNet Literary Quality Dataset |
| dc.type | corpus |
| metashare.ResourceInfo#ContentInfo.mediaType | text |
| has.files | yes |
| branding | CLARIN-DK |
| demo.uri | https://github.com/centre-for-humanities-computing/chicago_corpus |
| contact.person | Yuri; Bizzoni; yuri.bizzoni@gmail.com; Århus University |
| sponsor | N/A; N/A; N/A; nationalFunds; |
| size.info | 9089; items |
| files.size | 14207142 |
| files.count | 1 |
| annotationInfo.annotationType | POS and syntactic tags, sentiment and emotional arcs (8 emotions), semantic categories, readability, reader reaction, quality and reception |
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- Name
- CHICAGO_MEASURES_FEB24.xlsx
- Size
- 13.55 MB
- Format
- Microsoft Excel 2007
- Description
- dataset of intrinsic and extrinsic quality metrics
- MD5
- dbae19635d051bac7f269da1f42138dd