Social Media Sentiment and Stock Return: A Signaling Theory Explanation for Application of the Natural Langrage Processing Approaches
Download
Download
DownloadPreview
Social Media Sentiment and Stock Return_ A Signalling Theory Expl.pdf
- Published Version
(205kB)
| Preview
Available under license: Creative Commons Attribution Non-commercial
Export
Qin, Chuan, Miah, Shah Jahan 
ORCID: 0000-0002-3783-8769 and Shao, David
(2022)
Social Media Sentiment and Stock Return: A Signaling Theory Explanation for Application of the Natural Langrage Processing Approaches.
In: ACIS2022: Australasian Conference on Information Systems 2022, 4 December 2022 - 7 December 2022, Melbourne, Australia.
| Item type | Conference or Workshop Item (Paper) |
| URI | https://vuir.vu.edu.au/id/eprint/48094 |
| Official URL | https://aisel.aisnet.org/acis2022/31/ |
| Subjects | Current > FOR (2020) Classification > 4602 Artificial intelligence Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | social media sentiment; Natural Language Processing; signaling theory; stock return analysis |
| Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)