%0 Journal Article %A Zane Turner and Kevin Labille and Susan Gauch %D 2021 %J International Journal of Economics and Management Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 169, 2021 %T Lexicon-Based Sentiment Analysis for Stock Movement Prediction %U https://publications.waset.org/pdf/10011795 %V 169 %X Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We present a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change. %P 149 - 154