Papers by Khondoker Ittehadul Islam

2 papers
EmoNoBa: A Dataset for Analyzing Fine-Grained Emotions on Noisy Bangla Texts (2022.aacl-short)

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Challenge: EmoNoBa is a dataset for fine-grained emotion detection on Bangla text . it is based on 22698 comments from social media sites on 12 domains .
Approach: They propose a manually annotated dataset of 22,698 Bangla comments from social media sites on 12 different domains to use for fine-grained emotion detection.
Outcome: The proposed dataset of 22,698 public comments on 12 domains shows that hand-crafted features perform better than neural networks and pre-trained language models.
SentNoB: A Dataset for Analysing Sentiment on Noisy Bangla Texts (2021.findings-emnlp)

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Challenge: Bangla is the sixth most spoken language worldwide and the second Indo-Aryan language after Hindi.
Approach: They propose an annotated sentiment analysis dataset made of informally written Bangla texts.
Outcome: The proposed dataset is compared with neural networks and pretrained models . it shows that hand-crafted lexical features provide superior performance than neural networks .

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