Determination of Tesla Stock Fluctuations based on Tweet Sentiment Analysis using VADER
21st century is a digital notebook, where everything influences everything else. In such an era, a powerful microblogging such as Twitter is a sharp sword. Today, tweets don’t only make policies, they move markets. In this project, we employ the data from such a powerful microblogging tool to analyze how a tech giant, a global icon can influence the emotions of the millions connected, and in turn how these emotions play a role in the rise and fall of stocks of an Organization. Twitter, apart from being an amazing communication tool is an open mine for text and social web analysis. Here, we will be employing a dataset, consisting of tweets from one of the brightest Minds of 21st Century, Elon Musk to do a sentiment analysis and its impact on the stock prices of Tesla.
Objectives: • Extraction of Tweets from Twitter and Tesla Stock data • Implementation of a database containing Tweets and Stock Prices • Sentiment analysis on Tweets about Musk. • Trends of the stock prices of Tesla based on the tweets during that time and emotional reaction of the crowd towards such tweets
Packages to be installed:
- NLTK
- Pandas
- Numpy
- Matplotlib
- sqlite3
- VaderSentiment
- Plotly
To install packages: pip install <package_name>