IDEAS home Printed from https://ideas.repec.org/a/eee/reecon/v76y2022i3p170-188.html
   My bibliography  Save this article

To what extent do network effects moderate the relationship between social media propagated news and investors’ perceptions?

Author

Listed:
  • khan Feroz, Noushad
  • Hassan, Gazi
  • Cameron, Michael P.

Abstract

As a prominent social media tool, Twitter enables prompt dissemination of financial news and information, which can have a substantial impact on investors’ perceptions and decision-making processes. The propagation of financial news and information through Twitter can either positively or negatively affect investors’ perceptions. As per network theory, the impact of information on one's perception and behavior is known as the network effect. Since Twitter is also a network, we tried to contribute more to this theory in this study by considering other factors that can have an impact on the perceptions of investors. We argue that the impact of financial information and news on investors’ perceptions is moderated by other factors such as connectivity, social ties, and network size of the network. To establish the links between them, we considered three key factors in investors’ networks: (1) network connectivity (network structure); (2) social ties circle (friends, family, colleagues); and (3) size of the network (number of contacts). The results of this study indicate that highly connected investors receive more information and hence, the impact of news is derived from the connectivity of investors within the network. The findings of the study also show that the social ties circle plays a crucial role in determining the impact of the news. The findings further indicate that the impact of news on investors’ perceptions also depends on the theme of the news.

Suggested Citation

  • khan Feroz, Noushad & Hassan, Gazi & Cameron, Michael P., 2022. "To what extent do network effects moderate the relationship between social media propagated news and investors’ perceptions?," Research in Economics, Elsevier, vol. 76(3), pages 170-188.
  • Handle: RePEc:eee:reecon:v:76:y:2022:i:3:p:170-188
    DOI: 10.1016/j.rie.2022.07.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1090944322000308
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rie.2022.07.007?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.

    References listed on IDEAS

    as
    1. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    2. Pevzner, Mikhail & Xie, Fei & Xin, Xiangang, 2015. "When firms talk, do investors listen? The role of trust in stock market reactions to corporate earnings announcements," Journal of Financial Economics, Elsevier, vol. 117(1), pages 190-223.
    3. Conrad Murendo & Meike Wollni & Alan De Brauw & Nicholas Mugabi, 2018. "Social Network Effects on Mobile Money Adoption in Uganda," Journal of Development Studies, Taylor & Francis Journals, vol. 54(2), pages 327-342, February.
    4. Milla Siikanen & Kk{e}stutis Baltakys & Juho Kanniainen & Ravi Vatrapu & Raghava Mukkamala & Abid Hussain, 2017. "Facebook drives behavior of passive households in stock markets," Papers 1709.07300, arXiv.org, revised May 2018.
    5. Han N. Ozsoylev & Johan Walden & M. Deniz Yavuz & Recep Bildik, 2014. "Investor Networks in the Stock Market," Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1323-1366.
    6. Chung, San-Lin & Liu, Wenchien & Liu, Wen-Rang & Tseng, Kevin, 2018. "Investor network: Implications for information diffusion and asset prices," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 186-209.
    7. S. J. Liebowitz & Stephen E. Margolis, 1994. "Network Externality: An Uncommon Tragedy," Journal of Economic Perspectives, American Economic Association, vol. 8(2), pages 133-150, Spring.
    8. Gregory S. Miller & Douglas J. Skinner, 2015. "The Evolving Disclosure Landscape: How Changes in Technology, the Media, and Capital Markets Are Affecting Disclosure," Journal of Accounting Research, Wiley Blackwell, vol. 53(2), pages 221-239, May.
    9. H. Leibenstein, 1950. "Bandwagon, Snob, and Veblen Effects in the Theory of Consumers' Demand," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 64(2), pages 183-207.
    10. Swati Prasad & Ravi Kiran & Rakesh Kumar Sharma, 2021. "Influence of financial literacy on retail investors' decisions in relation to return, risk and market analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2548-2559, April.
    11. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    12. A. Seetharaman & Indu Niranjan & Nitin Patwa & Amit Kejriwal, 2017. "A Study of the Factors Affecting the Choice of Investment Portfolio by Individual Investors in Singapore," Accounting and Finance Research, Sciedu Press, vol. 6(3), pages 153-153, August.
    13. Cade, Nicole L., 2018. "Corporate social media: How two-way disclosure channels influence investors," Accounting, Organizations and Society, Elsevier, vol. 68, pages 63-79.
    14. Baker, H Kent & Haslem, John A, 1974. "Toward the Development of Client-Specified Valuation Models," Journal of Finance, American Finance Association, vol. 29(4), pages 1255-1263, September.
    15. Siikanen, Milla & Baltakys, Kęstutis & Kanniainen, Juho & Vatrapu, Ravi & Mukkamala, Raghava & Hussain, Abid, 2018. "Facebook drives behavior of passive households in stock markets," Finance Research Letters, Elsevier, vol. 27(C), pages 208-213.
    16. Arun Sundararajan & Foster Provost & Gal Oestreicher-Singer & Sinan Aral, 2013. "Research Commentary ---Information in Digital, Economic, and Social Networks," Information Systems Research, INFORMS, vol. 24(4), pages 883-905, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Santiago, Andrea & Pandey, Shweta & Manalac, Ma. Theresa, 2019. "Family presence, family firm reputation and perceived financial performance: Empirical evidence from the Philippines," Journal of Family Business Strategy, Elsevier, vol. 10(1), pages 49-56.
    2. Baltakys, Kȩstutis & Baltakienė, Margarita & Kärkkäinen, Hannu & Kanniainen, Juho, 2019. "Neighbors matter: Geographical distance and trade timing in the stock market," Finance Research Letters, Elsevier, vol. 31(C).
    3. Jin, Xuejun & Zhu, Yu & Huang, Ying Sophie, 2019. "Losing by learning? A study of social trading platform," Finance Research Letters, Elsevier, vol. 28(C), pages 171-179.
    4. Baltakienė, Margarita & Kanniainen, Juho & Baltakys, Kęstutis, 2021. "Identification of information networks in stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    5. Han, Rui-Qi & Li, Ming-Xia & Chen, Wei & Zhou, Wei-Xing & Stanley, H. Eugene, 2019. "Structural properties of statistically validated empirical information networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 747-756.
    6. Di Giuli, Alberta & Laux, Paul A., 2022. "The effect of media-linked directors on financing and external governance," Journal of Financial Economics, Elsevier, vol. 145(2), pages 103-131.
    7. Margarita Baltakienė & Kęstutis Baltakys & Juho Kanniainen & Dino Pedreschi & Fabrizio Lillo, 2019. "Clusters of investors around initial public offering," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-14, December.
    8. Amir, Rabah & Lazzati, Natalia, 2011. "Network effects, market structure and industry performance," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2389-2419.
    9. Wu, Yanling & Tian, Gary Gang, 2021. "Public relations expenditure, media tone, and regulatory decisions," Journal of Corporate Finance, Elsevier, vol. 66(C).
    10. Wang, Hu & Li, Shouwei & Ma, Yuyin, 2021. "Herding in Open-end Funds: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    11. Zhang, Tonghui & Yuan, Ying & Wu, Xi, 2020. "Is microblogging data reflected in stock market volatility? Evidence from Sina Weibo," Finance Research Letters, Elsevier, vol. 32(C).
    12. Wu, Chen-Hui, 2022. "The informativeness of brokerage reports: Privately-circulated versus publicly-disseminated news," International Review of Financial Analysis, Elsevier, vol. 83(C).
    13. Elizabeth Blankespoor & Ed Dehaan & John Wertz & Christina Zhu, 2019. "Why Do Individual Investors Disregard Accounting Information? The Roles of Information Awareness and Acquisition Costs," Journal of Accounting Research, Wiley Blackwell, vol. 57(1), pages 53-84, March.
    14. Takahashi, Takuma & Namiki, Fujio, 2003. "Three attempts at "de-Wintelization": Japan's TRON project, the US government's suits against Wintel, and the entry of Java and Linux," Research Policy, Elsevier, vol. 32(9), pages 1589-1606, October.
    15. Dunia López-Pintado & Duncan J. Watts, 2008. "Social Influence, Binary Decisions and Collective Dynamics," Rationality and Society, , vol. 20(4), pages 399-443, November.
    16. Chen, Xing & Wu, Chongfeng, 2022. "Retail investor attention and information asymmetry: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    17. John Kemp, 1999. "Spontaneous Change, Unpredictability and Consumption Externalities: a Dynamic Approach to Consumer Choice," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 2(3), pages 1-1.
    18. Kim, Jikyung (Jeanne) & Dong, Hang & Choi, Jeonghye & Chang, Sue Ryung, 2022. "Sentiment change and negative herding: Evidence from microblogging and news," Journal of Business Research, Elsevier, vol. 142(C), pages 364-376.
    19. Daniel Birke, 2009. "The Economics Of Networks: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 23(4), pages 762-793, September.
    20. Zhang, Tianjiao & Shen, Zhe & Sun, Qian, 2022. "Product market advertising and stock price crash risk," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).

    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:eee:reecon:v:76:y:2022:i:3:p:170-188. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622941 .

    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.