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SEACrowd/local_id_abusive

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The checks could not identify a recognised licence ID in the dataset's metadata.

Declared licence: Not declared in the tag or the card (see datasets with no declared licence)Evidence: README.md at a2f66b3
Licence files: LICENSE, licence not identifiedEvidence: LICENSE at a2f66b3
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

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Tasks

aspect-based-sentiment-analysis

Citation text from the card

@inproceedings{putri2021abusive,
  title={Abusive language and hate speech detection for Javanese and Sundanese languages in tweets: Dataset and preliminary study},
  author={Putri, Shofianina Dwi Ananda and Ibrohim, Muhammad Okky and Budi, Indra},
  booktitle={2021 11th International Workshop on Computer Science and Engineering, WCSE 2021},
  pages={461--465},
  year={2021},
  organization={International Workshop on Computer Science and Engineering (WCSE)},
  abstract={Indonesia’s demography as an archipelago with lots of tribes and local languages added variances in their communication style. Every region in Indonesia has its own distinct culture, accents, and languages. The demographical condition can influence the characteristic of the language used in social media, such as Twitter. It can be found that Indonesian uses their own local language for communicating and expressing their mind in tweets. Nowadays, research about identifying hate speech and abusive language has become an attractive and developing topic. Moreover, the research related to Indonesian local languages still rarely encountered. This paper analyzes the use of machine learning approaches such as Naïve Bayes (NB), Support Vector Machine (SVM), and Random Forest Decision Tree (RFDT) in detecting hate speech and abusive language in Sundanese and Javanese as Indonesian local languages. The classifiers were used with the several term weightings features, such as word n-grams and char n-grams. The experiments

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dataset_licence({ "id": "SEACrowd/local_id_abusive" })
signal: "unclear"
stated_licence: null
sources: 0