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How to measure the quality of financial tweets

Author

Listed:
  • Paola Cerchiello

    (Department of Economics and Management, University of Pavia)

  • Paolo Giudici

    (Department of Economics and Management, University of Pavia)

Abstract

Twitter text data may be very useful to predict financial tangibles, such as share prices, as well as intangible assets, such as company reputation. While twitter data are becoming widely available to researchers, methods aimed at selecting which twitter data are reliable are, to our knowledge, not yet available. To overcome this problem, and allow to employ twitter data for nowcasting and forecasting purposes, in this contribution we propose an effective statistical method that formalises and extends a quality index employed in the context of the evaluation of academic research: the h-index. Our proposal will be tested on a list of twitterers described by the Financial Times as "the top financial tweeters to follow", for the year 2013. Using our methodology we rank these twitterers and provide confidence intervals to decide whether they are significantly different.

Suggested Citation

  • Paola Cerchiello & Paolo Giudici, 2014. "How to measure the quality of financial tweets," DEM Working Papers Series 069, University of Pavia, Department of Economics and Management.
  • Handle: RePEc:pav:demwpp:069
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    References listed on IDEAS

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    1. Cerchiello, Paola & Giudici, Paolo, 2012. "On the distribution of functionals of discrete ordinal variables," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 2044-2049.
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    6. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, May.
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    8. Roberto Todeschini, 2011. "The j-index: a new bibliometric index and multivariate comparisons between other common indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 621-639, June.
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    Citations

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    Cited by:

    1. Paola Cerchiello & Paolo Giudici, 2014. "Financial big data analysis for the estimation of systemic risks," DEM Working Papers Series 086, University of Pavia, Department of Economics and Management.
    2. Paola Cerchiello & Giancarlo Nicola, 2018. "Assessing News Contagion in Finance," Econometrics, MDPI, vol. 6(1), pages 1-19, February.
    3. Ahelegbey, Daniel Felix & Cerchiello, Paola & Scaramozzino, Roberta, 2022. "Network based evidence of the financial impact of Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 81(C).
    4. Paola Cerchiello & Giancarlo Nicola, 2017. "Assessing News Contagion in Finance," DEM Working Papers Series 139, University of Pavia, Department of Economics and Management.
    5. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.

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