IDEAS home Printed from https://ideas.repec.org/a/taf/raaexx/v29y2022i6p1469-1496.html
   My bibliography  Save this article

Social media, interaction information and stock market efficiency: evidence from the Shenzhen stock exchange easy interaction platform in China

Author

Listed:
  • Qifa Xu
  • Qianqian Li
  • Cuixia Jiang
  • Jun Wu
  • Xin Zhang

Abstract

This paper studies the impact of interaction between investors and listed companies on market efficiency from two perspectives of earnings expectation and information asymmetry. We conduct an empirical analysis of the Shenzhen Stock Exchange Easy Interaction (SSEEI) platform. The interactive text is used to build interactivity indicators showing that the platform provides an important way to increase stock market efficiency. We further study how the interaction affects market efficiency using the emotion dictionary and the Latent Dirichlet Allocation (LDA) model. The results show that both good and bad news discussed on the platform are significant to market efficiency.

Suggested Citation

  • Qifa Xu & Qianqian Li & Cuixia Jiang & Jun Wu & Xin Zhang, 2022. "Social media, interaction information and stock market efficiency: evidence from the Shenzhen stock exchange easy interaction platform in China," Asia-Pacific Journal of Accounting & Economics, Taylor & Francis Journals, vol. 29(6), pages 1469-1496, November.
  • Handle: RePEc:taf:raaexx:v:29:y:2022:i:6:p:1469-1496
    DOI: 10.1080/16081625.2020.1829976
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/16081625.2020.1829976
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/16081625.2020.1829976?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:raaexx:v:29:y:2022:i:6:p:1469-1496. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/raae20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.