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Bangla Sentiment Classification

This is a compiled version of sentiment analysis dataset collected from several sources for benchmarking purpose and reported in our work: Sentiment Classification in Bangla Textual Content: A Comparative Study. We provide data splits and benchmark results to compare with any future works.

Table of contents:

Datasets

Directory structure:

In the following directories we have data splits (train/dev/test) for different datasets.

  • data/ABSA_Datasets -- This dataset has developed to perform aspect based sentiment analysis task in Bangla.
  • data/SAIL_data -- This dataset, consists of tweet posts, has developed in the Shared task on Sentiment Analysis in Indian Languages (SAIL) 2015. [2]
  • data/multichannel_bsentiment -- This data was collected from several newspapers, TV news, books, blogs, and social media.
  • data/youtube_sentiment -- This dataset was developed by extracting comments from various YouTube videos.
  • data/consolidated -- all combined dataset from the above data splits Note: Due to the license limitation we are not able to release CogniSenti Dataset.

Lexical Analysis

For the lexical analysis, we computed valance score for each dataset. In lexical_analysis/ directory, we provided such analyses.

Licensing

This is a compiled version from several datasets. We are releasing it as CC BY-NC-SA 2.0 (https://creativecommons.org/licenses/by-nc-sa/2.0/). However, for the respective data source please check the licence in the corresponding papers or source location.

Cite

Please cite the following papers if you are using the data:

  1. Alam, F., Hasan, M. A., Alam, T., Khan, A., Tajrin, J., Khan, N., & Chowdhury, S. A. (2021). A Review of Bangla Natural Language Processing Tasks and the Utility of Transformer Models. arXiv preprint arXiv:2107.03844.
  2. Md. Arid Hasan and Jannatul Tajrin and Shammur Absar Chowdhury and Firoj Alam, Sentiment Classification in Bangla Textual Content: A Comparative Study, 23rd International Conference on Computer and Information Technology (ICCIT), 2020.
  3. B. G. Patra, D. Das, A. Das, and R. Prasath, Shared task on sentiment analysis in indian languages (sail) tweets an overview, in Proc. of MIKE. Springer, 2015, pp. 650–655.
  4. M. Rahman, E. Kumar Dey et al., Datasets for aspect-based sentiment analysis in bangla and its baseline evaluation, Data, vol. 3, no. 2, p. 15, 2018.
  5. N. I. Tripto and M. E. Ali, “Detecting multilabel sentiment and emotions from bangla youtube comments,” in Proc. of ICBSLP. IEEE, 2018, pp. 1–6.
  6. M. Rezaul Karim, B. Raja Chakravarthi, M. Arcan, J. P. McCrae, and M. Cochez, Classification benchmarks for under-resourced Bengali language based on multichannel convolutional lstm network, arXiv, pp. arXiv–2004, 2020.
@article{alam2021review,
  title={A Review of Bangla Natural Language Processing Tasks and the Utility of Transformer Models},
  author={Alam, Firoj and Hasan, Md Arid and Alam, Tanvir and Khan, Akib and Tajrin, Janntatul and Khan, Naira and Chowdhury, Shammur Absar},
  journal={arXiv preprint arXiv:2107.03844},
  year={2021}
}
@inproceedings{iccit2020Arid,
	Author = {Md. Arid Hasan and Jannatul Tajrin and Shammur Absar Chowdhury and Firoj Alam},
	Booktitle = {23rd International Conference on Computer and Information Technology (ICCIT)},
	Month = {December},
	Title = {Sentiment Classification in Bangla Textual Content: A Comparative Study},
	Year = {2020}
}
@inproceedings{patra2015shared,
  title={Shared task on sentiment analysis in indian languages (sail) tweets-an overview},
  author={Patra, Braja Gopal and Das, Dipankar and Das, Amitava and Prasath, Rajendra},
  booktitle={Proc. of MIKE},
  pages={650--655},
  year={2015},
  organization={Springer}
}

@article{rahman2018datasets,
  title={Datasets for aspect-based sentiment analysis in bangla and its baseline evaluation},
  author={Rahman, Md and Kumar Dey, Emon and others},
  journal={Data},
  volume={3},
  number={2},
  pages={15},
  year={2018},
  publisher={Multidisciplinary Digital Publishing Institute}
}

@article{rezaul2020classification,
  title={Classification Benchmarks for Under-resourced {Bengali} Language based on Multichannel Convolutional-LSTM Network},
  author={Rezaul Karim, Md and Raja Chakravarthi, Bharathi and Arcan, Mihael and McCrae, John P and Cochez, Michael},
  journal={arXiv},
  pages={arXiv--2004},
  year={2020}
}
@inproceedings{tripto2018detecting,
  title={Detecting Multilabel Sentiment and Emotions from Bangla YouTube Comments},
  author={Tripto, Nafis Irtiza and Ali, Mohammed Eunus},
  booktitle={Proc. of ICBSLP},
  pages={1--6},
  year={2018},
  organization={IEEE}
}

Contact

Please write to [email protected].