Sentiment analysis of financial news using unsupervised approach
| Autor: | C. K. Jha, Aditi Sharan, Vikrant Vaish, Anita Yadav |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Orientation (computer vision)
Computer science business.industry InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Sentiment analysis Financial news 020206 networking & telecommunications 02 engineering and technology computer.software_genre ComputingMethodologies_ARTIFICIALINTELLIGENCE Domain (software engineering) ComputingMethodologies_DOCUMENTANDTEXTPROCESSING 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 020201 artificial intelligence & image processing Artificial intelligence business computer Natural language processing General Environmental Science |
| Zdroj: | Procedia Computer Science. 167:589-598 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2020.03.325 |
| Popis: | Sentiment analysis aims to determine the sentiment strength from a textual source for good decision making. This work focuses on application of sentiment analysis in financial news. The semantic orientation of documents is first calculated by tuning the existing technique for financial domain. The existing technique is found to have limitations in identifying representative phrases that effectively capture the sentiment of the text. Two alternative techniques - one using Noun-verb combinations and the other a hybrid one, are evaluated. Noun-verb approach yields best results in the experiment conducted. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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