Journal
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES 2019)
Volume 159, Issue -, Pages 1287-1294Publisher
ELSEVIER
DOI: 10.1016/j.procs.2019.09.298
Keywords
NLP; STOCK PREDICTION; DEEP LEARNING
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In this research, sentiment polarity identification model for finance is developed using fmancial and economic corpus and deep learning. Specifically, Japanese Economy Watchers Survey is used for the corpus and our model accuracy is high. Then the model is applied to evaluate news sentiment for predicting stock return. Our results confirmed that our model captures more news sentiment compared to using common polarity dictionary. (C) 2019 The Authors. Published by Elsevier B.V.
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