This is a repost from TradeTheSentiment.com
In October 2014, I successfully defended my dissertation titled “Analysis of Twitter Messages for Sentiment and Insight for use in Stock Market Decision Making.” This dissertation was the final step in earning more D.Sc. in Information Systems.
In my dissertation, I reported on my research into using natural language processing (NLP) to perform sentiment analysis on Twitter messages. This sentiment is then analyzed to determine if this sentiment can be used for stock market investing decisions using the idea of the Bear/Bull ratio which is a quantitative measure of sentiment from Twitter. The research conducted for my dissertation is the baseline for the services on this website.
You can view a video of my dissertation defense below (or click over to Vimeo to watch it there). Additionally, I’ve created a PDF version of my dissertation and I’ve listed it for sale on my Trade The Sentiment website for $50 per copy. You can purchase this dissertation and read up on some of the research that is the basis of this site by buying a copy for yourself. on this site. When you purchase a copy, you’ll have access to download a PDF version of my dissertation. To purchase a copy for yourself, you can click here and use Paypal or Stripe to buy a copy.
Note: If you are an academic research or doctoral student, please contact me directly and I’ll share a copy of my dissertation for free.
Using Twitter Sentiment in the Stock Market from Eric D Brown on Vimeo.
One response to “Using Twitter Sentiment for Market Decisions”
[…] Another example can be found with my doctorate work. When I was looking for a topic for my dissertation I was told by many people to just ‘pick something because you’ll never revisit the work’. That was terrible advice for me…if I was going to spend time working on something, I wanted to get some value from it. So…I chose to look at combining my interest in the financial markets with my interest in social media and sentiment analysis. This led to my dissertation titled “Analysis of Twitter Messages for Sentiment and Insight for use in Stock Market Decision Making.” […]