--- license: apache-2.0 annotations_creators: - expert-generated language_creators: - found task_categories: - token-classification language: - ro multilinguality: - monolingual source_datasets: - readerbench/ro-offense tags: - hate-speech-detection task_ids: - hate-speech-detection pretty_name: RO-Offense-Sequences size_categories: - 1K - **Homepage:** [https://github.com/readerbench/ro-offense-sequences](https://github.com/readerbench/ro-offense-sequences) - **Repository:** [https://github.com/readerbench/ro-offense-sequences](https://github.com/readerbench/ro-offense-sequences) - **Point of Contact:** [Teodora-Andreea Ion](mailto:theoion21.andr@gmail.com) - ### Dataset Summary a novel Romanian language dataset for offensive sequence detection with manually annotated offensive sequences from a local Romanian sports news website (gsp.ro): Resulting in 4800 annotated messages ### Languages Romanian ## Dataset Structure ### Data Instances An example of 'train' looks as follows. ``` { 'id': 5, 'text':'PLACEHOLDER TEXT', 'offensive_substrings': ['substr1','substr2'], 'offensive_sequences': [(0,10), (16,20)] } ``` ### Data Fields - `id`: The unique comment ID, corresponding to the ID in [RO Offense](https://huggingface.co./datasets/readerbench/ro-offense) - `text`: full comment text - `offensive_substrings`: a list of offensive substrings. Can contain duplicates if some offensive substring appears twice - `offensive_sequences`: a list of tuples with (start, end) position of the offensive sequences *Attention*: the sequences are computed for \n line sepparator! Git might convert the csv to \r\n. ### Data Splits | name |train|validate|test| |---------|----:|---:|---:| |ro|4,000|400|400| ## Dataset Creation ### Curation Rationale Collecting data for abusive language classification for Romanian Language. ### Source Data Sports News Articles comments #### Initial Data Collection and Normalization #### Who are the source language producers? Sports News Article readers ### Annotations #### Annotation process #### Who are the annotators? Native speakers ### Personal and Sensitive Information The data was public at the time of collection. PII removal has been performed. ## Considerations for Using the Data ### Social Impact of Dataset The data definitely contains abusive language. The data could be used to develop and propagate offensive language against every target group involved, i.e. ableism, racism, sexism, ageism, and so on. ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information This data is available and distributed under Apache-2.0 license ### Citation Information ``` tbd ``` ### Contributions