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Sentiment Analysis of Mixed Code for the Transliterated Hindi and Marathi Texts

https://doi.org/10.2139/ssrn.3429694
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inferred← citeshttps://doi.org/10.1007/978-3-031-47224-4_23openalex-snapshot
Sentiment Analysis: Indian Languages Perspective
inferred← citeshttps://doi.org/10.1007/978-3-031-53827-8_2openalex-snapshot
Adopting Pre-trained Large Language Models for Regional Language Tasks: A Case Study
inferred← citeshttps://doi.org/10.1007/978-981-97-5703-9_57openalex-snapshot
Sentiment Analysis of Marathi Texts Using Deep Learning Models
inferred← citeshttps://doi.org/10.1007/s13278-022-00877-wopenalex-snapshot
Supervised classifiers with TF-IDF features for sentiment analysis of Marathi tweets
inferred← citeshttps://doi.org/10.1016/j.knosys.2022.108668openalex-snapshot
An enhanced guided LDA model augmented with BERT based semantic strength for aspect term extraction in sentiment analysis
inferred← citeshttps://doi.org/10.1145/3548457openalex-snapshot
A Survey on NLP Resources, Tools, and Techniques for Marathi Language Processing
inferred← citeshttps://doi.org/10.18653/v1/2020.semeval-1.183openalex-snapshot
Zyy1510 Team at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text with Sub-word Level Representations
inferred← citeshttps://doi.org/10.3390/bdcc4010003openalex-snapshot
Opinion-Mining on Marglish and Devanagari Comments of YouTube Cookery Channels Using Parametric and Non-Parametric Learning Models
inferred← citeshttps://doi.org/10.36948/ijfmr.2024.v06i02.18964openalex-snapshot
Sentence Modelling with Convolutional Neural Networks for Enhancing Natural Language Understanding: A Comprehensive Exploration
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