Bitcoin is a form of electronic cash with no governing financial institution which can be used for online transactions or as an exchange between any two parties. In recent years Bitcoin has taken over the world by storm. According to a study, there have been over 100 Million investors in bitcoin with 668 Million transactions up till now. Much like the stock market, different techniques are applied for forecasting so as to know when to buy or sell the cryptocurrency in order to gain maximum profit. The cryptocurrency market has been volatile from the beginning but the last few months have been particularly a wild ride. There are numerous factors that contribute to its volatility that also makes the market challenging to predict accurately. One of the prime factors that contribute to its volatility is that Bitcoin does not have a central governing authority and is controlled by the general public. For this reason, its price is affected by socially constructed opinions. Primarily there are three techniques that are used to predict the market. Fundamental Analysis, Technical Analysis, and Lastly Sentiment Analysis. Using these three techniques we can have better insights for forecasting. Sentiment analysis is a technique through which a piece of text can be analyzed to determine the sentiment behind it. It combines machine learning and natural language processing (NLP) to achieve this. In regard to this context, Sentiments can arise from public opinion, let them be opinions of government officials, celebrities, experts, or any person that is influenced by this world. When it comes to influencing the public Twitter has the potential to be more influential, more than Facebook; especially when it comes to the dissemination of news. Scientists are increasingly recognizing Twitter's predictive power for a wide range of events, and particularly for financial markets [1] There are several hundreds of million bitcoin-related tweets, most of them spreading the news about how bitcoin is performing and speculations about how it will perform in the future. The idea is to use various machine learning techniques to find any correlation between public opinion and the actual price fluctuation and then actually forecasting the price fluctuation as these tweets continue to happen.
Tweet sentiment analysis is an active field for studies in price forecasting. Using Twitter in sentiment analysis for Bitcoin has gained researchers interest in it, due to the large amount of news feeds per minute regarding Bitcoin. Our aim is to try improving over existing research works, with various machine learning and deep learning models by trying different methodologies and features. Furthermore, with the outcome of our research work we will provide a platform for Realtime bitcoin forecasting based on sentiments of tweets.
● See the impact of tweets on BTC price
● Realtime bitcoin forecasting of btc using twitter sentiments
