Analysing market sentiment in financial news using lexical approach

Business and financial news bring us the latest information about the stock market. Studies have shown that business and financial news have a strong correlation with future stock performance. Therefore, extracting sentiments and opinions from business and financial news is useful as it may assist in the stock price predictions. In this paper, we present a sentiment analyser for financial news articles using lexicon-based approach. We use polarity lexicon to identify the positive or negative polarity of each term in the corpus. We conducted two sets of experiment using non-stemming tokens and stemming tokens by considering individual word found in the newspaper. The preliminary results are presented and discussed in this paper.