Bitcoin Movement Prediction Using Sentimental Analysis of Twitter Feeds - Thanekar, Atharva; Shelar, Sanket; Thakare, Aditya; Yadav, Vivek (International Journal of Computer Sciences and Engineering, 2019)
Bitcoin has recently attracted lots of attention in various sectors like economics, computer science, and many others due to its nature of combining encryption technology and monetary units. Now-a-days social media is perfectly representing the public sentiment and opinion about Trending events. Especially, twitter has attracted a plenty of attention from analyst for studying the public sentiments. Bitcoin prediction on the basis of general public sentiments tweeted on twitter has been an intriguing field of research. This paper aims to see how well the change in Bitcoin prices, the ups and downs, is correlated with the public opinions being expressed in tweets. Understanding people’s opinion from a text tweet is the objective of sentiment analysis. Sentiment analysis and machine learning algorithms are going to be applied to the tweets which are captured from twitter and analyse the correlation between Bitcoin movements and sentiments in tweets. In an elaborate way, positive tweets in social media about a Bitcoin are expected to encourage people to invest in the crypto currency and as a result the Bitcoin price would increase.