---
annotations_creators: []
language_creators: []
language:
- si
- en
license: 
- mit
multilinguality:
- multilingual
size_categories: []
source_datasets: []
task_categories:
- text-classification
task_ids:
- sentiment-analysis
- hate-speech-detection
- humor-detection
- language-identification
- aspect-identification
---

# Sinhala-English-Code-Mixed-Code-Switched-Dataset

This dataset contains 10,000 comments that have been annotated at the sentence level for sentiment analysis, humor detection, hate speech detection, aspect identification, and language identification.

The following is the tag scheme.
* Sentiment -  Positive, Negative, Neutral,  Conflict
* Humor - Humorous, Non humorous
* Hate Speech - Hate-Inducing, Abusive, Not offensive
* Aspect - Network, Billing or Price, Package, Customer Service, Data, Service or product, None
* Language ID - Sinhala, English, Sin-Eng, Eng-Sin, Mixed, Named-Entity, Symbol

If this datsaet is used, please give due credit by citing
Rathnayake, Himashi, et al. "Adapter-based fine-tuning of pre-trained multilingual language models for code-mixed and code-switched text classification." Knowledge and Information Systems 64.7 (2022): 1937-1966.

Other papers that use this dataset:
Rathnayake, Himashi, et al. "AdapterFusion-based multi-task learning for code-mixed and code-switched text classification." Engineering Applications of Artificial Intelligence 127 (2024): 107239.

Udawatta, Pasindu, et al. "Use of prompt-based learning for code-mixed and code-switched text classification." World Wide Web 27.5 (2024): 63.