Name
Title | ||
|---|---|---|
A Deep Learning-Based Approach to Constructing a Domain Sentiment Lexicon: a Case Study in Financial Distress Prediction |
Abstract | ||
|---|---|---|
•Proposing a novel lexicon generating approach for sentiment analysis that integrates word embedding models with deep learning-based classifiers.•Constructing financial domain sentiment lexicon in Chinese context is significant for analyzing related financial issues in China.•Chinese financial domain sentiment lexicon (CFDSL) generated by this study contains four aspects of sentiment words, namely capital markets, stock markets, companies’ internal business conditions, and politics.•Experiments prove that sentiment features extracted through CFDSL can independently achieve relatively satisfactory predictive performance in terms of financial distress prediction. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.ipm.2021.102673 | Information Processing & Management |
Keywords | DocType | Volume |
Domain sentiment lexicon,Financial text mining,Deep learning,Financial distress prediction,Word vector | Journal | 58 |
Issue | ISSN | Citations |
5 | 0306-4573 | 3 |
PageRank | References | Authors |
0.59 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shixuan Li | 1 | 3 | 0.59 |
| Wenxuan Shi | 2 | 7 | 3.67 |
| Jiancheng Wang | 3 | 3 | 0.59 |
| Heshen Zhou | 4 | 3 | 0.59 |