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Senior Project (CSCI 4391)

Using Twitter Sentiment Analysis to Predict Stock Market Simple Moving Averages

Abstract

We are seeking to explore the relationship between stock market-related sentiment and movements within the US stock market, we collected a sample of 28,000 tweets using the key hashtag, #stockmarket during an 11-day period in July 2018. Since the advent of the Internet and near-real time information to the layman, an industry of day traders have cropped up as they use this and new technology tools in an attempt to stay one-step ahead in the game. We intend to determine if Twitter is one of these research tools for these days traders and if so, what influence does it have on the market itself. Simple Moving Averages have been used for years by investors to determine trends in the stock market, is there a correlation to the overall mood on Twitter to the mood on Wall Street? After processing our data, we intend to match this information up with the actual movements of the market. Taking the five FAANG (Facebook, Apple, Amazon, Netflix, and Google) stocks along with the tweets in our data set that mention them to try determine if there is a cause and effect where the tweet potentially moved the stock price up or down or was the tweet in response to a previous market movement.

License

Copyright 2021 Leonard Box

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific langua