Analysing market sentiment in financial news using lexical approach

Author

Tan Li Im ; Phang Wai San ; Chin Kim On ; Alfred, Rayner ; Anthony, Philip

Author_Institution

Center of Excellent in Semantic Agents, Univ. Malaysia Sabah, Sabah, Malaysia

fYear

2013

fDate

2-4 Dec. 2013

Firstpage

145

Lastpage

149

Abstract

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.

Keywords

information analysis; pricing; publishing; stock markets; business news; financial news articles; lexical approach; market sentiment analysis; newspaper; nonstemming tokens; opinion extraction; sentiment analyser; sentiment extraction; stemming tokens; stock market; stock performance; stock price predictions; Accuracy; Algorithm design and analysis; Business; Conferences; Open systems; Prediction algorithms; Standards; Lexicon; Market Analysis; Sentiment Analysis; stock market prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Open Systems (ICOS), 2013 IEEE Conference on

Conference_Location

Kuching

Print_ISBN

978-1-4799-3152-1

Type

conf

DOI

10.1109/ICOS.2013.6735064

Filename

6735064