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--- |
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license: cc-by-nc-sa-4.0 |
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task_categories: |
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- text-classification |
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language: |
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- de |
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pretty_name: GerMS-AT |
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size_categories: |
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- 1K<n<10K |
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--- |
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# German Misogyny/Sexsim - Austria (GerMS-AT) Dataset |
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## Summary |
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This dataset contains user comments from an Austrian online newspaper. |
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The comments have been annotated by 4 or more out of 11 annotators |
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as to how strong sexism/mysogyny is present in the comment. |
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For each comment, the code of the annotator and the label assigned is given for all |
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annotators which have annotated that comment. Labels represent the severity of any |
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sexism/misogyny present in the comment from 0 (none), |
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1 (mild), 2 (present), 3 (strong) to 4 (severe). |
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The dataset contains 7984 comments. We provide the data using the same split as was used for |
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the [GermEval2024 GerMS-Detect shared task](https://ofai.github.io/GermEval2024-GerMS/) with |
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a training set of 5998 comments and a test set of 1986 comments. No dev set is provided as the |
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choice of dev set may be best left to the machine learning researcher/engineer. |
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A unique propery of this corpus is that it contains only a small portion of sexist/misogynyst remarks |
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which use strong language, curse-words or otherwise blatantly offending terms, a large number |
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of comments contain more subtle, indirect or at times ambiguous forms of sexism/misogyny. |
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## Data Structure |
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All comments are in a single JSONL file, one comment per line with the following properties: |
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* JSONL File: each line contains the JSON representation of a map |
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* Each map contains the information for one comment |
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* The map contains the following fields |
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* `text`: the text of the comment. The text may contain umlauts or other special characters and may contain arbitrary whitespace, newlines or carriage return charachters |
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* `annotations`: a list of maps, each map containing the fields "user" (the code of the annotator which provided the label) and "label" (the label assigned, see below). |
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* `round`: comments were annotated in rounds of 100, this gives the round identifier as a string containing a two-digit round number, e.g. "00" or "13" |
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* `source`: the code which identifies how comments which are likely negative and positive examples where selected for the annotation round |
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### Annotator codes - the following table shows the possible annotator codes and the number of comments annotated by each of them for the Train, Test and |
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combined data: |
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| Annotator code | Train | Test | All | |
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| -- | --: | --: | --: | |
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| A001 | 970 | 328 | 1298 | |
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| A002 | 5998 | 1986 | 7984 | |
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| A003 | 1242 | 456 | 1698 | |
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| A004 | 1394 | 504 | 1898 | |
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| A005 | 1552 | 542 | 2094 | |
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| A007 | 1246 | 451 | 1697 | |
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| A008 | 1849 | 649 | 2498 | |
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| A009 | 2923 | 971 | 3894 | |
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| A010 | 5998 | 1986 | 7984 | |
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| A011 | 927 | 114 | 1041 | |
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| A012 | 5998 | 1661 | 7659 | |
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Annotor IDs are anonymized and deliberately do not give demographic information. Among the 11 annotators there were |
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4 male and 7 female annotators. There were 7 annotators who are content moderators and 4 annotators who are not. |
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## Language |
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The comments are from a German (mostly Austrian variant) language web site, but may contain English terms which are |
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commonly used by German speakers, quotes of English text or other non-German parts. |
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## Anonymization |
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No metatdata about the comments is provided, the date of when the comment was written is deliberately not provided. |
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The comment texts have been scanned automatically and manually for any occurrence of information about the username or |
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real name of a person. Any such occurrence has been replaced with the placeholder `{USER}`. In ambiguous cases where it was not |
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clear if a name refers to a user or e.g. somebody mentioned in the newspaper article, the name was replaced by the placeholder. |
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All mentions of web addresses / URLs were replaced with the placeholder `{URL}` |
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## Datasheet |
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See the detailled [datasheet](./datasheet.md) |
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## Papers |
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Brigitte Krenn, Johann Petrak, Marina Kubina, and Christian Burger. 2024. |
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_Germs-at: A sex-ism/misogyny dataset of forum comments from an Austrian online newspaper._ |
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In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 7728–7739. |
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``` |
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@inproceedings{krenn2024, |
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title={{GERMS-AT}: A Sexism/Misogyny Dataset of Forum Comments from an {A}ustrian Online Newspaper}, |
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author={Krenn, Brigitte and Petrak, Johann and Kubina, Marina and Burger, Christian}, |
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booktitle={Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)}, |
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pages={7728--7739}, |
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year={2024} |
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} |
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``` |
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NOTE: other than described in this paper, the current version of the corpus contains more annotations from additional annotators, has 11 comments removed |
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which consistet only of an URL and/or USER name, and has additional mentions of user names anonymized. |
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