Detecting tweet sentiment and sarcasm on online learning during covid-19

Detecting tweet sentiment and sarcasm on online learning during covid-19

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Manylion Llyfryddiaeth
Prif Awduron:	Das, Shishir Kumar, Nisa, Khairun, Kabir, Razit, Tonni, Israt Jahan
Awduron Eraill:	Chakrabarty, Dr. Amitabha
Fformat:	Traethawd Ymchwil
Iaith:	English
Cyhoeddwyd:	Brac University 2024
Pynciau:	Data mining Machine learning Tweet Sarcasm Prediction Decision tree Linear regression analysis Online learning Computational linguistics. Natural language processing (Computer science)
Mynediad Ar-lein:	http://hdl.handle.net/10361/22718

Eitemau Tebyg

Intelligent assisted living in pregnancy
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Weather forecasting using Deep Learning
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Predicting the length of stay in a hospital for a particular disease using machine learning algorithms
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A novel approach to reduce air pollution through machine learning based PM2.5 prediction
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A machine learning approach to detect depression and anxiety using supervised learning
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Early grade prediction using profile data
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Evaluating user influence in Twitter based on hashtags using data mining
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Detecting online recruitment fraud by using machine learning
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Where will you setup your business next?: a machine learning approach to suggest ideal geographical location for new restaurant establishment
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Application of machine learning techniques on the context of livestock analysis
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Predicting stock market movement using sentiment analysis of twitter feed
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Finding ideal geographical location for businesses using machine learning technique
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Heart disease prediction using techniques of classification in machine learning
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Predicting a T20 cricket match result while the match is in progress
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Polycystic ovary syndrome detection using neural network.
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Data analysis on the Bangladesh share market using Machine-Learning
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Machine learning based analysis and prediction of crop yield and prices of Aman, Aus and Boro rice
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A supervised learning approach by machine learning and deep learning algorithms to predict type II DM risk
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An implementation and analysis of deep learning models for the detection of wheat diseases
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Supershop management Models: An optimised way to manage the supershop using hyperautomation and machine learning
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A counseling system to predict the study path for freshmen
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Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
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The applications of data mining and machine learning in Bangladesh for disease pattern analysis and prediction
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Implementation of machine learning to estimate the air pollutants such as Carbon dioxide, methane, nitrous oxide and total greenhouse gas emissions in Bangladesh
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Amazon product reviews sentiment analysis using supervised learning algorithms
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A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
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Stock price prediction
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Social media sentiment study on COVID-19 outbreak
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Modelling and forecasting energy demand of Bangladesh using AI based algorithms
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Flood prediction using machine learning models
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Analyzing area-wise air pollution level using machine learning for a better future
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Prediction of bipolar disorder from mental episodes using machine learning approach
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An advanced hospital rating system using machine learning and natural language processing
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A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
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Forecasting stock market prices using advanced tools of machine learning
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Cyhoeddwyd: (2019)