Social media trend analysis to predict the success of products using deep learning technique

Social media trend analysis to predict the success of products using deep learning technique

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Xehetasun bibliografikoak
Egile Nagusiak:	Khan, Farden Ehsan, Ruhan, Ahmed Mahir, Shamsuddin, Rifat
Beste egile batzuk:	Ashraf, Faisal Bin
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2023
Gaiak:	Social media Trend analysis Deep learning Sentiment analysis KNN Text mining MLP RoBERTa Random forest BART Decision Tree DistilBERT Social media > Economic aspects Machine learning
Sarrera elektronikoa:	http://hdl.handle.net/10361/21814

Antzeko izenburuak

Sentiment classification on Bengali food and restaurant reviews
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Quality assessment of extracted information from newspaper comment sections using natural language processing
nork: Deb, Arnob, et al.
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Predicting stock market movement using sentiment analysis of twitter feed
nork: Chakraborty, Pranjal, et al.
Argitaratua: (2017)

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A counseling system to predict the study path for freshmen
nork: Usha, Rowshni Tasneem, et al.
Argitaratua: (2019)

Sentiment analysis in Bengali Text using NLP
nork: Sarkar, Ankon, et al.
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A feature selection approach to determine obesity using machine learning method
nork: Antor, Shahidul Alam, et al.
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Predicting COVID-19 disease outcome and post-recovery conditions using machine learning
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A hybrid rumor detection model derived from a comparative study of supervised approaches
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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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nork: Rahee, Arnob, et al.
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Analyzing the security of e-Health data based on a hybrid federated learning model
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nork: Rony, Ismail Hossain, et al.
Argitaratua: (2020)

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nork: Pratanu, Abul Mushfique Muslah, et al.
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nork: Rodela, Raisa Rahman, et al.
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Analysis on the effects of wallstreetbets on the stock market
nork: Hossain, Abir, et al.
Argitaratua: (2022)

Text classification using machine learning algorithms
nork: Hasnat, Fahim, et al.
Argitaratua: (2018)

Social media terraforming media landscape
nork: Zayed, Abdullah
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SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
nork: Alam, Auninda, et al.
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Hate speech detection using machine learning techniques
nork: Manzoor, Tahbib, et al.
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An analytic framework on food trend of Dhaka city using social media reviews and real time data set
nork: Alif, Redwanul Alam
Argitaratua: (2017)

Predicting regional accents of Bengali language using deep learning
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The applications of data mining and machine learning in Bangladesh for disease pattern analysis and prediction
nork: Mahmud, Mahmudul Hasan
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Flood prediction using machine learning models
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nork: Nahar, Fatiha Binte Kamrun, et al.
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Cryptocurrency price prediction using Social Media Data Mining and Epidemic Modeling
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Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
nork: Tasnim, Anika, et al.
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Parking data analysis
nork: Ahamed, Kasfi, et al.
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A color vision approach considering Reflection Co efficient based on Autoencoder techniques using deep neural networks
nork: Mahmud, Shakib Izaz, et al.
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Prediction of bipolar disorder from mental episodes using machine learning approach
nork: Tasmeem, Sumaiya, et al.
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Modelling and forecasting energy demand of Bangladesh using AI based algorithms
nork: Mahmud, Booshra Nazifa, et al.
Argitaratua: (2019)

Heart disease prediction using techniques of classification in machine learning
nork: Afrose, Sadia, et al.
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