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- Publisher Website: 10.1287/isre.2019.0910
- Scopus: eid_2-s2.0-85104372110
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Article: Fake News, Investor Attention, and Market Reaction
Title | Fake News, Investor Attention, and Market Reaction |
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Authors | |
Keywords | fake news investor attention financial technology textual analysis social media |
Issue Date | 2021 |
Publisher | INFORMS. The Journal's web site is located at http://isr.pubs.informs.org |
Citation | Information Systems Research, 2021, v. 32 n. 1, p. 35-52 How to Cite? |
Abstract | Does fake news in financial markets attract more investor attention and have a significant impact on stock prices? We use the U.S. Securities and Exchange Commission (SEC) crackdown of stock promotion schemes in April 2017 to examine investor attention and the stock price reaction to fake news articles. Using data from Seeking Alpha, we find that fake news stories generate significantly more attention than a control sample of legitimate articles. We find no evidence that article commenters can detect fake news, and we also find that Seeking Alpha editors have only modest ability to detect fake news. However, we show that machine learning algorithms can successfully identify fake news from linguistic features of the article. The stock market appears to price fake news correctly. While abnormal trading volume increases around the release of fake news, the increase is less than that observed for legitimate news. The stock price reaction to fake news is discounted when compared with legitimate news articles. |
Persistent Identifier | http://hdl.handle.net/10722/284479 |
ISSN | 2023 Impact Factor: 5.0 2023 SCImago Journal Rankings: 4.176 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Clarke, J | - |
dc.contributor.author | Chen, H | - |
dc.contributor.author | Du, D | - |
dc.contributor.author | Hu, YJ | - |
dc.date.accessioned | 2020-08-07T08:58:13Z | - |
dc.date.available | 2020-08-07T08:58:13Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Information Systems Research, 2021, v. 32 n. 1, p. 35-52 | - |
dc.identifier.issn | 1047-7047 | - |
dc.identifier.uri | http://hdl.handle.net/10722/284479 | - |
dc.description.abstract | Does fake news in financial markets attract more investor attention and have a significant impact on stock prices? We use the U.S. Securities and Exchange Commission (SEC) crackdown of stock promotion schemes in April 2017 to examine investor attention and the stock price reaction to fake news articles. Using data from Seeking Alpha, we find that fake news stories generate significantly more attention than a control sample of legitimate articles. We find no evidence that article commenters can detect fake news, and we also find that Seeking Alpha editors have only modest ability to detect fake news. However, we show that machine learning algorithms can successfully identify fake news from linguistic features of the article. The stock market appears to price fake news correctly. While abnormal trading volume increases around the release of fake news, the increase is less than that observed for legitimate news. The stock price reaction to fake news is discounted when compared with legitimate news articles. | - |
dc.language | eng | - |
dc.publisher | INFORMS. The Journal's web site is located at http://isr.pubs.informs.org | - |
dc.relation.ispartof | Information Systems Research | - |
dc.subject | fake news | - |
dc.subject | investor attention | - |
dc.subject | financial technology | - |
dc.subject | textual analysis | - |
dc.subject | social media | - |
dc.title | Fake News, Investor Attention, and Market Reaction | - |
dc.type | Article | - |
dc.identifier.email | Chen, H: chen19@hku.hk | - |
dc.identifier.authority | Chen, H=rp02520 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1287/isre.2019.0910 | - |
dc.identifier.scopus | eid_2-s2.0-85104372110 | - |
dc.identifier.hkuros | 311979 | - |
dc.identifier.volume | 32 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 35 | - |
dc.identifier.epage | 52 | - |
dc.identifier.isi | WOS:000640102400003 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1047-7047 | - |