How to measure the quality of financial tweets

Paola Cerchiello () and Paolo Giudici

No 69, DEM Working Papers Series from University of Pavia, Department of Economics and Management

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.

Pages: 22 pages
Date: 2014-02
New Economics Papers: this item is included in nep-ecm and nep-for
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Citations: View citations in EconPapers (5)

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