IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2312.11530.html
   My bibliography  Save this paper

Twitter Permeability to financial events: an experiment towards a model for sensing irregularities

Author

Listed:
  • Ana Fern'andez Vilas
  • Rebeca P. D'iaz Redondo
  • Keeley Crockett
  • Majdi Owda
  • Lewis Evans

Abstract

There is a general consensus of the good sensing and novelty characteristics of Twitter as an information media for the complex financial market. This paper investigates the permeability of Twittersphere, the total universe of Twitter users and their habits, towards relevant events in the financial market. Analysis shows that a general purpose social media is permeable to financial-specific events and establishes Twitter as a relevant feeder for taking decisions regarding the financial market and event fraudulent activities in that market. However, the provenance of contributions, their different levels of credibility and quality and even the purpose or intention behind them should to be considered and carefully contemplated if Twitter is used as a single source for decision taking. With the overall aim of this research, to deploy an architecture for real-time monitoring of irregularities in the financial market, this paper conducts a series of experiments on the level of permeability and the permeable features of Twitter in the event of one of these irregularities. To be precise, Twitter data is collected concerning an event comprising of a specific financial action on the 27th January 2017:{~ }the announcement about the merge of two companies Tesco PLC and Booker Group PLC, listed in the main market of the London Stock Exchange (LSE), to create the UK's Leading Food Business. The experiment attempts to answer five key research questions which aim to characterize the features of Twitter permeability to the financial market. The experimental results confirm that a far-impacting financial event, such as the merger considered, caused apparent disturbances in all the features considered, that is, information volume, content and sentiment as well as geographical provenance. Analysis shows that despite, Twitter not being a specific financial forum, it is permeable to financial events.

Suggested Citation

  • Ana Fern'andez Vilas & Rebeca P. D'iaz Redondo & Keeley Crockett & Majdi Owda & Lewis Evans, 2023. "Twitter Permeability to financial events: an experiment towards a model for sensing irregularities," Papers 2312.11530, arXiv.org.
    • Handle: RePEc:arx:papers:2312.11530
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2312.11530
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Feng Xiong & Kim MacKenzie, 2015. "The business use of Twitter by Australian listed companies," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(6), pages 421-428, Special I.
    2. 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.
    3. Ali Tafti & Ryan Zotti & Wolfgang Jank, 2016. "Real-Time Diffusion of Information on Twitter and the Financial Markets," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-16, August.
    4. Gabriele Ranco & Darko Aleksovski & Guido Caldarelli & Miha Grčar & Igor Mozetič, 2015. "The Effects of Twitter Sentiment on Stock Price Returns," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-21, September.
    5. Zheludev, Ilya & Smith, Robert & Aste, Tomaso, 2014. "When can social media lead financial markets?," LSE Research Online Documents on Economics 57376, London School of Economics and Political Science, LSE Library.
    6. Timm O. Sprenger & Andranik Tumasjan & Philipp G. Sandner & Isabell M. Welpe, 2014. "Tweets and Trades: the Information Content of Stock Microblogs," European Financial Management, European Financial Management Association, vol. 20(5), pages 926-957, November.
    7. Feng Xiong & Kim MacKenzie, 2015. "The business use of Twitter by Australian listed companies," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(5), pages 421-428, Special I.
    8. Billett, Matthew T. & Yu, Miaomiao, 2016. "Asymmetric Information, Financial Reporting, and Open-Market Share Repurchases," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(4), pages 1165-1192, August.
    9. Sanjiv Sabherwal & Salil K. Sarkar & Ying Zhang, 2011. "Do Internet Stock Message Boards Influence Trading? Evidence from Heavily Discussed Stocks with No Fundamental News," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(9-10), pages 1209-1237, November.
    10. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    11. Bart Hobijn & Boyan Jovanovic, 2001. "The Information-Technology Revolution and the Stock Market: Evidence," American Economic Review, American Economic Association, vol. 91(5), pages 1203-1220, 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. Renault, Thomas, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 25-40.
    2. Peter Gabrovšek & Darko Aleksovski & Igor Mozetič & Miha Grčar, 2017. "Twitter sentiment around the Earnings Announcement events," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-21, February.
    3. 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.
    4. Xiong, Xiong & Meng, Yongqiang & Joseph, Nathan Lael & Shen, Dehua, 2020. "Stock mispricing, hard-to-value stocks and the influence of internet stock message boards," International Review of Financial Analysis, Elsevier, vol. 72(C).
    5. Eierle, Brigitte & Klamer, Sebastian & Muck, Matthias, 2022. "Does it really pay off for investors to consider information from social media?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    6. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    7. Kommel, Karl Arnold & Sillasoo, Martin & Lublóy, Ágnes, 2019. "Could crowdsourced financial analysis replace the equity research by investment banks?," Finance Research Letters, Elsevier, vol. 29(C), pages 280-284.
    8. Yu, Jing-Rung & Chiou, W. Paul & Hung, Cing-Hung & Dong, Wen-Kuei & Chang, Yi-Hsuan, 2022. "Dynamic rebalancing portfolio models with analyses of investor sentiment," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 1-13.
    9. Arezoo Hatefi Ghahfarrokhi & Mehrnoush Shamsfard, 2019. "Tehran Stock Exchange Prediction Using Sentiment Analysis of Online Textual Opinions," Papers 1909.03792, arXiv.org, revised Sep 2019.
    10. Kraaijeveld, Olivier & De Smedt, Johannes, 2020. "The predictive power of public Twitter sentiment for forecasting cryptocurrency prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    11. Rui Fan & Oleksandr Talavera & Vu Tran, 2020. "Social media bots and stock markets," European Financial Management, European Financial Management Association, vol. 26(3), pages 753-777, June.
    12. Li, Zhuolei & Diao, Xundi & Wu, Chongfeng, 2022. "The influence of mobile trading on return dispersion and herding behavior," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    13. Yingying Xu & Zhixin Liu & Jichang Zhao & Chiwei Su, 2017. "Weibo sentiments and stock return: A time-frequency view," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-21, July.
    14. Arezoo Hatefi Ghahfarrokhi & Mehrnoush Shamsfard, 2020. "Tehran stock exchange prediction using sentiment analysis of online textual opinions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(1), pages 22-37, January.
    15. Agarwal, Shweta & Kumar, Shailendra & Goel, Utkarsh, 2019. "Stock market response to information diffusion through internet sources: A literature review," International Journal of Information Management, Elsevier, vol. 45(C), pages 118-131.
    16. Dong, Hang & Gil-Bazo, Javier, 2020. "Sentiment stocks," International Review of Financial Analysis, Elsevier, vol. 72(C).
    17. Francisco Guijarro & Ismael Moya-Clemente & Jawad Saleemi, 2019. "Liquidity Risk and Investors’ Mood: Linking the Financial Market Liquidity to Sentiment Analysis through Twitter in the S&P500 Index," Sustainability, MDPI, vol. 11(24), pages 1-13, December.
    18. Yongqiang Meng & Dehua Shen & Xiong Xiong & Jorgen Vitting Andersen, 2020. "A Socio-Finance Model: The Case of Bitcoin," Documents de travail du Centre d'Economie de la Sorbonne 20031, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    19. He, Xue-Zhong & Li, Kai & Santi, Caterina & Shi, Lei, 2022. "Social interaction, volatility clustering, and momentum," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 125-149.
    20. Thomas Renault, 2020. "Sentiment analysis and machine learning in finance: a comparison of methods and models on one million messages," Digital Finance, Springer, vol. 2(1), pages 1-13, September.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2312.11530. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.