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Journal of Discrete Mathematical Sciences and Cryptography Volume 25, 2022 - Issue 7: Sustainable Communication and Security
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Research Article

A hybrid convolutional long short-term memory (CNN-LSTM) based natural language processing (NLP) model for sentiment analysis of customer product reviews in Bangla

Mahbuba Rahman Purba1 Department of Computer Science and Engineering, International University of Business Agriculture and Technology (IUBAT), 4 Embankment Drive Road, Sector 10 Uttara Model Town, Dhaka1230, BangladeshCorrespondence[email protected]
,
Moniya Akter2 Department of Computer Science and Engineering, International University of Business Agriculture and Technology (IUBAT), 4 Embankment Drive Road, Sector 10 Uttara Model Town, Dhaka1230, Bangladesh E-mail: [email protected]
,
Rubayea Ferdows3 Department of Computer Science and Engineering, International University of Business Agriculture and Technology (IUBAT), 4 Embankment Drive Road, Sector 10 Uttara Model Town, Dhaka1230, Bangladesh E-mail: [email protected]
&
Fuad Ahmed4 Department of Computer Science and Engineering, Islamic University of Technology (IUT), Boardbazar, Gazipur, Bangladesh E-mail: [email protected]
Pages 2111-2120 | Published online: 08 Dec 2022

References

  • Ferdows, Rubayea, et al. “Exploring Causal Effect of Personal Financial Activities by Social Media Influences.” 2021 24th International Conference on Computer and Information Technology (ICCIT). IEEE, 2021.
  • “Bengali language” Wikipedia: The Free Encyclopedia. Wikimedia Foundation, Inc, 22 July 2004, en.wikipedia.org/wiki/Bengali_language. Accessed 10 Aug. 2004.
  • Van Atteveldt, Wouter, Mariken ACG Van der Velden, and Mark Boukes. “The validity of sentiment analysis: Comparing manual annotation, crowd-coding, dictionary approaches, and machine learning algorithms.” Communication Methods and Measures 15.2 (2021): 121-140. doi: 10.1080/19312458.2020.1869198
  • Rudkowsky, Elena, et al. “More than bags of words: Sentiment analysis with word embeddings.” Communication Methods and Measures 12.2-3 (2018): 140-157. doi: 10.1080/19312458.2018.1455817
  • Modha, Sandip, Prasenjit Majumder, and Thomas Mandl. “An empirical evaluation of text representation schemes to filter the social media stream.” Journal of Experimental & Theoretical Artificial Intelligence 34.3 (2022): 499-525. doi: 10.1080/0952813X.2021.1907792
  • Li, Xianyong, et al. “A Novel Deep Learning-based Sentiment Analysis Method Enhanced with Emojis in Microblog Social Networks.” Enterprise Information Systems (2022): 1-22. doi: 10.1080/17517575.2022.2037160
  • Bhowmik, Nitish Ranjan, et al. “Bangla text sentiment analysis using supervised machine learning with extended lexicon dictionary.” Natural Language Processing Research 1.3-4 (2021): 34–45. doi: 10.2991/nlpr.d.210316.001
  • Ahmed, Fuad, et al. “AutoCl: A Visual Interactive System for Automatic Deep Learning Classifier Recommendation Based on Models Performance.” arXiv preprint arXiv:2202.11928 (2022).
  • Hemal, Asif Uddin Ahmed, et al. “Human Hostility Detection through Visual Data Using Deep learning.” 2022 The 28th International Workshop on Frontiers of Computer Vision (IW-FCV) (2022): 162-169.
  • Chowdhury, Shaika, and Wasifa Chowdhury. “Performing Sentiment Analysis in Bangla Microblog Posts.” 2014 International Conference on Informatics, Electronics & Vision (ICIEV). IEEE, 2014.
  • Hassan, Asif et al. “Sentiment analysis on bangla and romanized bangla text using deep recurrent models.” 2016 International Workshop on Computational Intelligence (IWCI) (2016): 51-56.
  • Mehndiratta, Pulkit, and Devpriya Soni. “Identification of sarcasm using word embeddings and hyperparameters tuning.” Journal of Discrete Mathematical Sciences and Cryptography 22.4 (2019): 465-489. doi: 10.1080/09720529.2019.1637152
  • Feng, Rui, Congcong Yang, and Yunhua Qu. “A word embedding model for analyzing patterns and their distributional semantics.” Journal of Quantitative Linguistics 29.1 (2022): 80-105. doi: 10.1080/09296174.2020.1767481
  • Mikolov, Tomas, et al. “Efficient estimation of word representations in vector space.” arXiv preprint arXiv:1301.3781 (2013).
  • Verma, Vivek Kumar, et al. “Dissecting word embeddings and language models in natural language processing.” Journal of Discrete Mathematical Sciences and Cryptography 24.5 (2021): 1509-1515. doi: 10.1080/09720529.2021.1968108

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