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Role of Discourse Information in Urdu Sentiment Classification

https://doi.org/10.1145/3300050
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Do we need hundreds of classifiers to solve real world classification problems

What points at this work

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

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A comparative study of sentiment analysis in urdu and roman urdu: the neglected realms
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A Language model-based approach to sentiment classification of languages in central Asia
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UTSA: Urdu Text Sentiment Analysis Using Deep Learning Methods
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Speech Databases, Speech Features, and Classifiers in Speech Emotion Recognition: A Review
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Knowledge Based Nested Frames of Discernment for Target Integrated Identification
inferred← citeshttps://doi.org/10.1109/icacccn51052.2020.9362761openalex-snapshot
Syntactically and Semantically Annotated Hindi Corpus for an Opinion Mining System
inferred← citeshttps://doi.org/10.1109/icacs60934.2024.10473232openalex-snapshot
Sentiment Analysis From Urdu Language-based Text using Deep Learning Techniques
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A Technique to Calculate National Happiness Index by Analyzing Roman Urdu Messages Posted on Social Media
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An Unsupervised Approach for Sentiment Analysis on Social Media Short Text Classification in Roman Urdu
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UrduAI: Writeprints for Urdu Authorship Identification
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Towards Enhanced Identification of Emotion from Resource-Constrained Language through a novel Multilingual BERT Approach
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Multiclass Event Classification from Text
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Deep Learning and Machine Learning-Based Model for Conversational Sentiment Classification
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Sentiment Analysis of Roman Urdu on E-Commerce Reviews Using Machine Learning
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Extraction of Opinion Target Using Syntactic Rules in Urdu Text
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Contextually Enriched Meta-Learning Ensemble Model for Urdu Sentiment Analysis
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A Systematic Study of Urdu Language Processing its Tools and Techniques: A Review
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Sentiment analysis techniques, challenges, and opportunities: Urdu language-based analytical study
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