News or Noise? Using Twitter to Identify and Understand Company-specific News Flow
- Publication type:
- Journal article
- Metadata:
-
- Autoren
- Timm O Sprenger
- Philipp G Sandner
- Andranik Tumasjan
- Isabell M Welpe
- Autoren-URL
- https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000343814200001&DestLinkType=FullRecord&DestApp=WOS_CPL
- DOI
- 10.1111/jbfa.12086
- eISSN
- 1468-5957
- Externe Identifier
- Clarivate Analytics Document Solution ID: AR8GQ
- ISSN
- 0306-686X
- Ausgabe der Veröffentlichung
- 7-8
- Zeitschrift
- JOURNAL OF BUSINESS FINANCE & ACCOUNTING
- Schlüsselwörter
- event study
- news events
- information leakage
- market reaction
- computational linguistics
- Paginierung
- 791 - 830
- Datum der Veröffentlichung
- 2014
- Status
- Published
- Titel
- News or Noise? Using Twitter to Identify and Understand Company-specific News Flow
- Sub types
- Article
- Ausgabe der Zeitschrift
- 41
Data source: Web of Science (Lite)
- Other metadata sources:
-
- Abstract
- <jats:title>Abstract</jats:title><jats:p>This study presents a methodology for identifying a broad range of real‐world news events based on microblogging messages. Applying computational linguistics to a unique dataset of more than 400,000 S&P 500 stock‐related Twitter messages, we distinguish between good and bad news and demonstrate that the returns prior to good news events are more pronounced than for bad news events. We show that the stock market impact of news events differs substantially across different categories.</jats:p>
- Autoren
- Timm O Sprenger
- Philipp G Sandner
- Andranik Tumasjan
- Isabell M Welpe
- DOI
- 10.1111/jbfa.12086
- eISSN
- 1468-5957
- ISSN
- 0306-686X
- Ausgabe der Veröffentlichung
- 7-8
- Zeitschrift
- Journal of Business Finance & Accounting
- Sprache
- en
- Online publication date
- 2014
- Paginierung
- 791 - 830
- Datum der Veröffentlichung
- 2014
- Status
- Published
- Herausgeber
- Wiley
- Herausgeber URL
- http://dx.doi.org/10.1111/jbfa.12086
- Datum der Datenerfassung
- 2023
- Titel
- News or Noise? Using Twitter to Identify and Understand Company‐specific News Flow
- Ausgabe der Zeitschrift
- 41
Data source: Crossref
- Abstract
- This study presents a methodology for identifying a broad range of real-world news events based on microblogging messages. Applying computational linguistics to a unique dataset of more than 400,000 S&P 500 stock-related Twitter messages, we distinguish between good and bad news and demonstrate that the returns prior to good news events are more pronounced than for bad news events. We show that the stock market impact of news events differs substantially across different categories.
- Autoren
- Timm O Sprenger
- Philipp G Sandner
- Andranik Tumasjan
- Isabell M Welpe
- Ausgabe der Veröffentlichung
- 7-8
- Zeitschrift
- Journal of Business Finance & Accounting
- Paginierung
- 791 - 830
- Datum der Veröffentlichung
- 2014
- Titel
- News or Noise? Using Twitter to Identify and Understand Company-specific News Flow
- Ausgabe der Zeitschrift
- 41
Data source: RePEc
- Beziehungen:
- Property of