Sentiment analysis using R: an approach to correlate bitcoin price fluctuations with change in user sentiments

Sentiment analysis using R: an approach to correlate bitcoin price fluctuations with change in user sentiments

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.

Xehetasun bibliografikoak
Egile Nagusiak:	Rahman, Shaomi, Hemel, Jonayed Nafis, Anta, Syed Junayed Ahmed, Al Muhee, Hossain
Beste egile batzuk:	Uddin, Jia
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	BRAC University 2018
Gaiak:	Bitcoin Price fluctuations User sentiments Sentiment analysis R programmimg language
Sarrera elektronikoa:	http://hdl.handle.net/10361/10163

Antzeko izenburuak

Analyzing users’ sentiment towards video games based on reviews from microblog
nork: Roy, Abhijeet, et al.
Argitaratua: (2018)

Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations
nork: Rabbi, Md. Nafis
Argitaratua: (2024)

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

Microblog sentiment analysis for rating TV shows
nork: Abdullah, Ashik
Argitaratua: (2017)

Sentiment analysis on mobile operators’ customer review
nork: Hossain, Mohammed Mohibul, et al.
Argitaratua: (2020)

Sentiment analysis for Bengali newspaper headlines
nork: Hossain, Mohammad Samman, et al.
Argitaratua: (2017)

A multimodal approach of sentiment analysis to predict customer emotions towards a product
nork: Islam, Shadman, et al.
Argitaratua: (2020)

A transformer based approach to detect the sentiment of drivers in ride sharing platforms
nork: Chakraborty, Sovon
Argitaratua: (2024)

Forecasting bitcoin price considering macro economic factors and media influence using bidirectional LSTM and random forest regressor as ensemble model
nork: Ghose, Swattic, et al.
Argitaratua: (2023)

Amazon product reviews sentiment analysis using supervised learning algorithms
nork: Hawladar, Mohibullah, et al.
Argitaratua: (2021)

Sentimental analysis on political speeches
nork: Atiq, Asif, et al.
Argitaratua: (2022)

Performing sentiment analysis in Bangla microblog posts
nork: Chowdhury, Shaika, et al.
Argitaratua: (2017)

Product rating generation based on public opinion using sentiment analysis
nork: Rabbi, Reshan Ahmed, et al.
Argitaratua: (2018)

Feature based mobile phone rating using sentiment analysis and machine learning approaches
nork: Kafi, Abdullahil, et al.
Argitaratua: (2018)

Optimizing restaurant recommendations through sentiment analysis
nork: Juha, Tasnia, et al.
Argitaratua: (2024)

Embedded system based bangla intelligent social virtual robot with sentiment analysis
nork: Hossain, Md. Ishan Arefin, et al.
Argitaratua: (2018)

Sentimental analysis of customer product Reviews to understand customer needs using machine learning
nork: Symum, Md Abdullah Al, et al.
Argitaratua: (2023)

An effective machine learning approach for sentiment analysis of restaurant reviews
nork: Karim, Rabita
Argitaratua: (2018)

Analyzing data of social media to evaluate customer behavior of companies using sentiment analysis
nork: Shourin, Bushra, et al.
Argitaratua: (2018)

Aspect-based sentiment analysis using SemEval and Amazon datasets
nork: Hasib, Tamanna, et al.
Argitaratua: (2018)

A sustainable Bitcoin architecture
nork: Monem, Maruf
Argitaratua: (2022)

A framework for sentiment analysis: a data-driven approach
nork: Islam, Md. Jahedul, et al.
Argitaratua: (2021)

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

Sentiment classification on Bengali food and restaurant reviews
nork: Hossain, Abid, et al.
Argitaratua: (2024)

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

Predicting stock market movement using sentiment analysis of twitter feed
nork: Chakraborty, Pranjal, et al.
Argitaratua: (2017)

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

Share market forecasting with LSTM neural network and sentimental trend prediction
nork: Rony, Ismail Hossain, et al.
Argitaratua: (2020)

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

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

Social media sentiment study on COVID-19 outbreak
nork: Karmaker, Anik, et al.
Argitaratua: (2021)

Sentiment analysis of customer reviews on food ordering portals of Bangladesh using natural language processing
nork: Deb, Priom, et al.
Argitaratua: (2024)

Into the heart of Bangla speech: advancing speech sentiment recognition with semi-supervised multimodal machine learning model leveraging an iterative SHAP-based feature selection
nork: Shruti, Abanti Chakraborty
Argitaratua: (2024)

Bitcoin price forecasting based on historical data
nork: Roy, Shaily, et al.
Argitaratua: (2018)

Fluctuating nonlinear oscillators

Inflation Dynamics in Advanced Economies : A Decomposition into Cyclical and Non-Cyclical Factors /
nork: Lian, Weicheng
Argitaratua: (2022)

Sentiments
nork: Matimba

Drift in Producer Price Indexes for the Former Soviet Union (FSU) Countries /
nork: Zieschang, Kimberly
Argitaratua: (1994)

A machine learning approach to predict movie box-office success
nork: Quader, Nahid, et al.
Argitaratua: (2018)

Sentimental Opera
nork: Stefano Castelvecchi
Argitaratua: (2013)