IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v67y2020ics105752191930273x.html
   My bibliography  Save this article

Sensitivity to sentiment: News vs social media

Author

Listed:
  • Gan, Baoqing
  • Alexeev, Vitali
  • Bird, Ron
  • Yeung, Danny

Abstract

We explore the rapidly changing social and news media landscape that is responsible for the dissemination of information vital to the efficient functioning of the financial markets. Using the sheer volume of social and news media activity, commonly known as buzz, we document three distinct regimes. We find that between 2011 and 2013 the news media coverage stimulates activity in social media. This is followed by a transition period of two-way causality. From 2016, however, changes in levels of social media activity seem to lead and generate news coverage volumes. We uncover similar evolution of lead-lag pattern between sentiment measures constructed from the tonality contained in textual data from social and news media posts. We discover that market variables exert stronger impact on investor sentiment than the other way around. We also find that return responses to social media sentiment almost doubled after the transition period, while return responses to news-based sentiment almost halved to its pre-transition level. The linkage between volatility and sentiment is much more persistent than that between returns and sentiment. Overall, our results suggest that social media is becoming the dominant media source.

Suggested Citation

  • Gan, Baoqing & Alexeev, Vitali & Bird, Ron & Yeung, Danny, 2020. "Sensitivity to sentiment: News vs social media," International Review of Financial Analysis, Elsevier, vol. 67(C).
    • Handle: RePEc:eee:finana:v:67:y:2020:i:c:s105752191930273x
    DOI: 10.1016/j.irfa.2019.101390
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S105752191930273X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.irfa.2019.101390?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Arcuri, Maria Cristina & Gandolfi, Gino & Russo, Ivan, 2023. "Does fake news impact stock returns? Evidence from US and EU stock markets," Journal of Economics and Business, Elsevier, vol. 125.
    2. Yousaf, Imran & Youssef, Manel & Goodell, John W., 2022. "Quantile connectedness between sentiment and financial markets: Evidence from the S&P 500 twitter sentiment index," International Review of Financial Analysis, Elsevier, vol. 83(C).
    3. Zhang, Hongwei & Hong, Huojun & Guo, Yaoqi & Yang, Cai, 2022. "Information spillover effects from media coverage to the crude oil, gold, and Bitcoin markets during the COVID-19 pandemic: Evidence from the time and frequency domains," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 267-285.
    4. Liu, Qingbai & Wang, Chuanjie & Zhang, Ping & Zheng, Kaixin, 2021. "Detecting stock market manipulation via machine learning: Evidence from China Securities Regulatory Commission punishment cases," International Review of Financial Analysis, Elsevier, vol. 78(C).
    5. Banerjee, Ameet Kumar & Akhtaruzzaman, Md & Dionisio, Andreia & Almeida, Dora & Sensoy, Ahmet, 2022. "Nonlinear nexus between cryptocurrency returns and COVID-19 news sentiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    6. Wang, Xinjie & Xiang, Zhiqiang & Xu, Weike & Yuan, Peixuan, 2022. "The causal relationship between social media sentiment and stock return: Experimental evidence from an online message forum," Economics Letters, Elsevier, vol. 216(C).
    7. Filip, Angela Maria & Pochea, Maria Miruna, 2023. "Intentional and spurious herding behavior: A sentiment driven analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    8. Alomari, Mohammad & Al Rababa’a, Abdel Razzaq & El-Nader, Ghaith & Alkhataybeh, Ahmad & Ur Rehman, Mobeen, 2021. "Examining the effects of news and media sentiments on volatility and correlation: Evidence from the UK," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 280-297.
    9. Wang, Gaoshan & Yu, Guangjin & Shen, Xiaohong, 2021. "The effect of online environmental news on green industry stocks: The mediating role of investor sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    10. Piñeiro-Chousa, Juan & López-Cabarcos, M.Ángeles & Caby, Jérôme & Šević, Aleksandar, 2021. "The influence of investor sentiment on the green bond market," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    11. Piñeiro-Chousa, Juan & López-Cabarcos, M. Ángeles & Šević, Aleksandar, 2022. "Green bond market and Sentiment: Is there a switching Behaviour?," Journal of Business Research, Elsevier, vol. 141(C), pages 520-527.
    12. Zin Yau Heng & Henry Leung, 2023. "The role of option‐based information on StockTwits, options trading volume, and stock returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(8), pages 1091-1125, August.
    13. Banerjee, Ameet Kumar & Dionisio, Andreia & Pradhan, H.K. & Mahapatra, Biplab, 2021. "Hunting the quicksilver: Using textual news and causality analysis to predict market volatility," International Review of Financial Analysis, Elsevier, vol. 77(C).
    14. Shuyi Li & Junhao Kong & Stefan Cristian Gherghina, 2022. "News Sentiment and the Risk of a Stock Price Crash Risk: Based on Financial Dictionary Combined BERT-DCA," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-28, July.
    15. Fedorova, E. & Pyltsin, I. & Kovalchuk, Yu. & Drogovoz, P., 2022. "News and social networks of Russian companies: Degree of influence on the securities market," Journal of the New Economic Association, New Economic Association, vol. 53(1), pages 32-52.
    16. Yuna Hao & Behrang Vand & Benjamin Manrique Delgado & Simone Baldi, 2023. "Market Manipulation in Stock and Power Markets: A Study of Indicator-Based Monitoring and Regulatory Challenges," Energies, MDPI, vol. 16(4), pages 1-28, February.
    17. Yongan Xu & Jianqiong Wang & Zhonglu Chen & Chao Liang, 2023. "Sentiment indices and stock returns: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1063-1080, January.
    18. Dong, Hang & Gil-Bazo, Javier, 2020. "Sentiment stocks," International Review of Financial Analysis, Elsevier, vol. 72(C).
    19. Esteban Serrano-Monge, 2022. "Inferences from Portfolio Theory and Efficient Market Hypothesis to the Impact of Social Media on Sovereign Debt: Colombia, Ecuador, and Peru," JRFM, MDPI, vol. 15(4), pages 1-16, March.
    20. Marmora, Paul, 2021. "Individual investor ownership and the news coverage premium," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 494-507.
    21. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
    22. Xiaohong Shen & Gaoshan Wang & Yue Wang & Alfred Peris, 2021. "The Influence of Research Reports on Stock Returns: The Mediating Effect of Machine-Learning-Based Investor Sentiment," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-14, December.
    23. Wu, Chunying & Xiong, Xiong & Gao, Ya, 2022. "The role of different information sources in information spread: Evidence from three media channels in China," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 327-341.
    24. Chou, Ke-Hsin & Day, Min-Yuh & Chiu, Chien-Liang, 2023. "Do bitcoin news information flow and return volatility fit the sequential information arrival hypothesis and the mixture of distribution hypothesis?," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 365-385.
    25. Ben Chamberlain & Zhangxin (Frank) Liu & Lee A. Smales, 2023. "Short interest and the stock market relation with news sentiment from traditional and social media sources," Australian Economic Papers, Wiley Blackwell, vol. 62(2), pages 321-334, June.

    More about this item

    Keywords

    Investor sentiment; Textual analysis; Vector autoregressive (VAR) model; Thomson Reuters MarketPsych Indices (TRMI);
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G40 - Financial Economics - - Behavioral Finance - - - General
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

    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:eee:finana:v:67:y:2020:i:c:s105752191930273x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    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.