ktoufiquee/NC-SentNoB

This is a multilabel dataset used for Noise Identification purpose in the paper "A Comparative Analysis of Noise Reduction Methods in Sentiment Analysis on Noisy Bangla Texts" accepted in 2024 The 9th Workshop on Noisy and User-generated Text (W-NUT) collocated with EACL 2024.

• Annotated by 4 native Bangla speakers with 90% trustworthiness score.
• Fleiss' Kappa Score: 0.69

Definition of noise categories

Type	Definition
Local Word	Any regional words even if there is a spelling error.
Word Misuse	Wrong use of words or unnecessary repetitions of words.
Context/Word Missing	Not enough information or missing words.
Wrong Serial	Wrong order of the words.
Mixed Language	Words in another language. Foreign words that were adopted into the Bangla language over time are excluded from this type.
Punctuation Error	Improper placement or missing punctuation. Sentences ending without "।" were excluded from this type.
Spacing Error	Improper use of white space.
Spelling Error	Words not following spelling of Bangla Academy Dictionary.
Coined Word	Emoji, symbolic emoji, link.
Others	Noises that do not fall into categories mentioned above.

Statistics of NC-SentNoB per noise class

Class	Instances	#Word/Instance
Local Word	2,084 (0.136%)	16.05
Word Misuse	661 (0.043%)	18.55
Context/Word Missing	550 (0.036%)	13.19
Wrong Serial	69 (0.005%)	15.30
Mixed Language	6,267 (0.410%)	17.91
Punctuation Error	5,988 (0.391%)	17.25
Spacing Error	2,456 (0.161%)	18.78
Spelling Error	5,817 (0.380%)	17.30
Coined Words	549 (0.036%	15.45
Others	1,263 (0.083%)	16.52

Heatmap of correlation coefficient

Citation

If you use the datasets, please cite the following paper:

@misc{elahi2024comparative,
      title={A Comparative Analysis of Noise Reduction Methods in Sentiment Analysis on Noisy Bangla Texts}, 
      author={Kazi Toufique Elahi and Tasnuva Binte Rahman and Shakil Shahriar and Samir Sarker and Md. Tanvir Rouf Shawon and G. M. Shahariar},
      year={2024},
      eprint={2401.14360},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}