Using Social Media and Google Search Data to Forecast Crude Oil Prices

Opinions expressed by users on social media and Internet search
activity are a valuable source of information. Recently a literature
emerged to use this information to forecast financial markets in general
and the crude oil market in specific.

This project contributes to this literature. Data and information from
various sources including Twitter as well as Google Trends is used to
forecast crude oil prices. Forecasting techniques based on traditional
time series analysis are combined with methods such as sentiment
analysis, a sub-discipline within the fields of natural language
processing (NLP) and computational linguistics.

This project requires excellent skills in the following areas:

- time series applications
- organization of large data-sets
- programming skills

Applicants interested in this research project should submit a more detailed research proposal (of a maximum of 2000 words) that expands on the broad outline given abroad.