Ascertaining polarity of public opinions on Bangladesh cricket using machine learning techniques-Reference-Cited by-同舟云学术

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Ascertaining polarity of public opinions on Bangladesh cricket using machine learning techniques

Published:2021-04-18 Issue: Volume: Page:
ISSN:2366-3286
Container-title:Spatial Information Research
language:en
Short-container-title:Spat. Inf. Res.

Author:

Faruque M. Abdullah,Rahman Saifur,Chakraborty Partha,Choudhury Tanupriya^ORCID,Um Jung-Sup,Singh Thipendra Pal

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computers in Earth Sciences,Computer Science Applications,Geography, Planning and Development

Link

https://link.springer.com/content/pdf/10.1007/s41324-021-00403-8.pdf

Reference20 articles.

1. Tuhin, R. A., Paul, B. K., Nawrine, F., Akter, M., & Das, A. K. (2019). An automated system of sentiment analysis from bangla text using supervised learning techniques. In 4th international conference on computer and communication systems (ICCCS) (pp. 360–364). IEEE.

2. Salehin S. M. S., Miah, R., & Islam, M. S. (2020). A comparative sentiment analysis on Bengali Facebook posts. In Proceedings of the international conference on computing advancements (ICCA) (pp. 1–8). Association for Computing Machinery.

3. Asthana, R., Dhanetwal, S., Choudhury, T., Tomar, R. (2020). Study of sentiment analysis in mental health using speech recognition and image to text conversion. In Computational intelligence in pattern recognition. advances in intelligent systems and computing (Vol. 1120). Springer. https://doi.org/10.1007/978-981-15-2449-3_9.

4. Kaur, H., Choudhury, T., Singh, T. P., & Shamoon, M. (2019). Crime analysis using text mining. In 2019 international conference on contemporary computing and informatics (IC3I) (pp. 283–288). https://doi.org/10.1109/IC3I46837.2019.9055606.

5. Rahman, S., & Chakraborty, P. (2020). Bangla document classification using deep recurrent neural network with BiLSTM. In Proceedings of international conference on machine intelligence and data science applications. https://doi.org/10.1007/978-981-33-4087-9_43.

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