Harry Bold Undergraduate Dissertation 2017/18

Sentiment Analysis of Financial Microblogs

Supervised by A.Vlachos

Abstract

For a stock trader social media is a great place to obtain information about people's towards a specific market move. However humans can only process these tweets one by one and therefore not got the full picture.

This is where sentiment analysis comes in. Sentiment analysis provides us with the capabilities to process large amounts of data and extract the opinions of the writers. In an environment where opinions are in the movement of stock prices, this can prove to be very valuable.

This project will experiment using different sentiment analysis methods on financial data in order to observe whcih techniques are most effective in the financial domain.