Sentiment analysis of online text articles

Abstract

Increasingly, sentiment analysis has proven to be invaluable in the past decade. Driven by the need to analyse the sentiment of large amounts of text data, a lot of development has been put into sentiment analysis. Ongoing efforts are still being put towards the creation of an automated process to produce a domain-specific corpus to support the sentiment analysis of the domain. This project explores the sentiment analysis of text in the financial domain, which is of particular interest as the sentiments of financial articles are deeply linked to the state of the current financial markets. For this project, the author investigated the techniques into the construction of a corpus and a semi-automated annotator to ease the said construction process. The corpus would be constructed with a particular focus in finance. In addition to the techniques, a front-end user interface has been created to allow easy usage of the sentiment analyser.