metadata

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<n<10K
extra_gated_prompt: >-
  Warning: this repository contains harmful content (abusive language, hate
  speech).

Dataset Card for "RO-Offense-Sequences"

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Homepage: https://github.com/readerbench/ro-offense-sequences
Repository: https://github.com/readerbench/ro-offense-sequences
Point of Contact: Teodora-Andreea Ion

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
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

Datasets:

readerbench
/

ro-offense-sequences