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A Novel Approach for Emotion Detection and Sentiment Analysis for Low Resource Urdu Language Based on CNN-LSTM

https://doi.org/10.3390/electronics11244096

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What this work says

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

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Accurate Online Social Network User Profiling

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Deep-EmoRU: mining emotions from roman urdu text using deep learning ensemble

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AlphaLogger: detecting motion-based side-channel attack using smartphone keystrokes

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Automatic emotion detection in text streams by analyzing Twitter data

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A GENERAL PSYCHOEVOLUTIONARY THEORY OF EMOTION

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Co-evolutionary competitive swarm optimizer with three-phase for large-scale complex optimization problem

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Ekman, emotional expression, and the art of empirical epiphany

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Deep Learning-Based Sentiment Analysis for Roman Urdu Text

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Multimodal analysis of speech and arm motion for prosody-driven synthesis of beat gestures

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Lexicon-based approach outperforms Supervised Machine Learning approach for Urdu Sentiment Analysis in multiple domains

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Information Granulation-Based Community Detection for Social Networks

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Urdu Sentiment Analysis Using Supervised Machine Learning Approach

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Current State of Text Sentiment Analysis from Opinion to Emotion Mining

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Emotion Detection from Text via Ensemble Classification Using Word Embeddings

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Emotion detection in Roman Urdu text using machine learning

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Roman Urdu reviews dataset for aspect based opinion mining

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CECL at SemEval-2019 Task 3: Using Surface Learning for Detecting Emotion in Textual Conversations

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EmoSense at SemEval-2019 Task 3: Bidirectional LSTM Network for Contextual Emotion Detection in Textual Conversations

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Deep Sentiment Analysis Using CNN-LSTM Architecture of English and Roman Urdu Text Shared in Social Media

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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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Exploring Low-Resource Urdu Speech Emotion Recognition Employing Siamese and CNN Models

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Urdu Sentiment Analysis: A Review

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A Transfer-Based Deep Learning Model for Persian Emotion Classification

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Intensified Emotion and Sentiment Annotation for Words, Emojis, and Slang in English

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Comparative Analysis of Advanced ML Techniques for Urdu Speech Emotion Recognition: An Acoustic Study in Low-Resource Languages*

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