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A Comprehensive Roadmap on Bangla Text-based Sentiment Analysis

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Semantic-Emotion Neural Network for Emotion Recognition From Text

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LSTM based Deep RNN Architecture for Election Sentiment Analysis from Bengali Newspaper

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Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Network

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Bengali VADER: A Sentiment Analysis Approach Using Modified VADER

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Sentiment Analysis from Depression-Related User-Generated Contents from Social Media

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Supervised approach of sentimentality extraction from bengali facebook status

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inferredcites →https://doi.org/10.1109/icict4sd50815.2021.9396882openalex-snapshot

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Depression detection using emotion artificial intelligence

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inferredcites →https://doi.org/10.1145/3377049.3377098openalex-snapshot

Identification of Extreme Guilt and Grave Fault in Bengali Language

inferredcites →https://doi.org/10.1145/3450447openalex-snapshot

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Multi-category Bangla News Classification using Machine Learning Classifiers and Multi-layer Dense Neural Network

inferredcites →https://doi.org/10.1515/jisys-2017-0398openalex-snapshot

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IRLab_DAIICT at SemEval-2020 Task 9: Machine Learning and Deep Learning Methods for Sentiment Analysis of Code-Mixed Tweets

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Cross-lingual sentiment classification in low-resource Bengali language

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Abusive content detection in transliterated Bengali-English social media corpus

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Emotion Classification in a Resource Constrained Language Using Transformer-based Approach

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Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis

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Performance Evaluation and Comparison using Deep Learning Techniques in Sentiment Analysis

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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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