Name
Title | ||
|---|---|---|
Predicting Sentence-Level Polarity Labels of Financial News Using Abnormal Stock Returns |
Abstract | ||
|---|---|---|
•We predict polarity labels of sentences in financial news based on stock returns.•Multi-instance learning to transfer information from documents to sentences.•Approach outperforms benchmark methods by 5.10% in terms of predictive accuracy.•Method assists investors and helps companies communicating their messages as intended. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.eswa.2020.113223 | Expert Systems with Applications |
Keywords | DocType | Volume |
Financial news,Expert systems,Natural language processing,Multi-instance learning,Decision-making | Journal | 148 |
Issue | ISSN | Citations |
C | 0957-4174 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bernhard Lutz | 1 | 1 | 2.03 |
| Nicolas Prollochs | 2 | 27 | 7.01 |
| Dirk Neumann | 3 | 294 | 37.29 |