Sentiment analysis using Natural Language Processing (NLP) & deep learning

Sentiment analysis using Natural Language Processing (NLP) & deep learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Bibliografiska uppgifter
Huvudupphovsmän:	Islam, Kazi Minhazul, Reza, Md. Safkat, Yeaser, MD. Samin
Övriga upphovsmän:	Islam, MD Saiful
Materialtyp:	Lärdomsprov
Språk:	English
Publicerad:	Brac University 2022
Ämnen:	NLP Deep learning Cyber bullying Racism Social media Prediction Bi-directional LSTM Machine learning Natural language processing (Computer science) Human-computer interaction
Länkar:	http://hdl.handle.net/10361/15823

Liknande verk

Identifying code-mixed and code-switched hateful remarks on social media using NLP
av: Sinha, Sumaiya, et al.
Publicerad: (2024)

Human sentiment analysis using natural language processing
av: Shamya, Md. Shamiul Haque Khan, et al.
Publicerad: (2024)

Hybrid recommendation system of intelligent captioning using deep learning networks
av: Wasi, Ahamed Al, et al.
Publicerad: (2024)

Stock Market Price movement prediction using RNN and Point-weight Sentiment
av: Uddin, S. M. Rageeb Noor, et al.
Publicerad: (2022)

Predicting suicidal intent from social media text post using machine learning
av: Chowdhury, Md. Mubin Ul Islam, et al.
Publicerad: (2023)

Sentiment analysis in Bengali Text using NLP
av: Sarkar, Ankon, et al.
Publicerad: (2023)

Predicting crime using deep learning
av: Shihab, Muhammad Nafees, et al.
Publicerad: (2024)

Comparative analysis of machine learning models for stock price analysis across different dataset sizes
av: Srabon, Abir Alam, et al.
Publicerad: (2023)

A hybrid deep learning model and explainable AI-based Bengali hate speech multi-label classification and interpretation
av: Shakil, Mahmudul Hasan
Publicerad: (2023)

RED-LSTM: Real time emotion detection using LSTM
av: Labiba, Mansura Rahman, et al.
Publicerad: (2023)

Prediction of anxiety and depression among the transgender in Bangladesh
av: Easha, Ishrat Jahan, et al.
Publicerad: (2023)

Predicting effectiveness of marketing through analyzing emotional context in advertisement using deep learning
av: Arafat, Sheikh Mohammad, et al.
Publicerad: (2021)

An implementation and analysis of deep learning models for the detection of wheat diseases
av: Zubair, Ahmad, et al.
Publicerad: (2024)

Multimodal fake news detection using text and image
av: Biswas, Trisha, et al.
Publicerad: (2024)

Health trauma and well-being assistant for Bengali seniors in household: a multimodal approach
av: Islam, Md. Nazmul, et al.
Publicerad: (2024)

Novel approach to detect hate speech and profanity on online platforms
av: Pritha, Barha Meherun, et al.
Publicerad: (2022)

An integrated approach: fake review detection using convBERT-BiLSTM classification
av: Mahmud, Md. Anas, et al.
Publicerad: (2024)

Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
av: Islam, Zahedul, et al.
Publicerad: (2023)

Predicting regional accents of Bengali language using deep learning
av: Ibrahim, Md. Abu, et al.
Publicerad: (2022)

A deep learning approach towards soft biometrics attributes prediction using CNN
av: Kibria, Maharab, et al.
Publicerad: (2022)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
av: Toufique, S.M, et al.
Publicerad: (2024)

Sentiment analysis to determine employee job satisfaction using machine learning techniques
av: Mouli, Nazifa, et al.
Publicerad: (2023)

Performance analysis of deep learning algorithms for Intrusion Detection System(IDS) of IoT Security
av: Fiha, Yeamin Jahan, et al.
Publicerad: (2022)

Detecting self-esteem level and depressive indication due to different parenting style using supervised learning techniques
av: Al Taawab, Abdullah, et al.
Publicerad: (2022)

Application of CNN based architectures in detection of distracted drivers
av: Arafin, Irfana, et al.
Publicerad: (2023)

Smart companion agent for mental well-being through Deep Learning and NLP
av: Khan, Rafiur, et al.
Publicerad: (2021)

Bang-lish sentiment classification using deep learning
av: Saleheen, Abrar, et al.
Publicerad: (2023)

Sentiment analysis on Bangladesh airlines review data using machine learning
av: Hasib, Khan Md.
Publicerad: (2022)

Deep learning approaches to EEG and fMRI data: a comparative study for sleep stage classification
av: Tanvir, Farhan, et al.
Publicerad: (2024)

Behavior change analysis due to violent video gaming using deep learning models
av: Rahman, Akhlak Ur, et al.
Publicerad: (2024)

Weather forecasting using Deep Learning
av: Fahad, Sheikh Abdul, et al.
Publicerad: (2023)

Real-time crime detection using convolutional LSTM and YOLOv7
av: Sakiba, Cyrus, et al.
Publicerad: (2023)

A modern technique to detect potholes by Computer Vision and Deep Learning
av: Saif, Muntasir Mahmud, et al.
Publicerad: (2023)

Damaged road detection using Image Processing and Deep Learning
av: Swadesh, Shimran Mahbub, et al.
Publicerad: (2022)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
av: Maliha, Miftahul Zannat, et al.
Publicerad: (2023)

Classification of peripheral blood cell images using deep learning
av: Aadi, Oyshik Ahmed, et al.
Publicerad: (2024)

Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
av: Tasnim, Anika, et al.
Publicerad: (2022)

A texture based industrial fault diagnosis model using Gammatone Filter Bank and transfer learning
av: Morshed, Atique, et al.
Publicerad: (2021)

Traffic sign recognition using deep learning
av: Amir, Afia Binte, et al.
Publicerad: (2020)

Violent activity detection through surveillance camera using deep learning
av: Miah, Parvez, et al.
Publicerad: (2023)