How to measure the quality of financial tweets

How to measure the quality of financial tweets Twitter text data may be very useful to evaluate from a different perspective 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 reliable twitter data are, to our knowledge, not yet available. To overcome this problem, and allow to employ twitter data for descriptive and predictive 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, renamed T 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. Moreover through a sentiment analysis, we employ the twitters content to estimate graphical models useful in the context of financial systemic risk. To this aim we focus on the Italian bank system and we show how listed banks are connected on the basis of tweets data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

How to measure the quality of financial tweets

Loading next page...
 
/lp/springer_journal/how-to-measure-the-quality-of-financial-tweets-DWboImFPnS
Publisher
Springer Netherlands
Copyright
Copyright © 2015 by Springer Science+Business Media Dordrecht
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-015-0229-6
Publisher site
See Article on Publisher Site

Abstract

Twitter text data may be very useful to evaluate from a different perspective 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 reliable twitter data are, to our knowledge, not yet available. To overcome this problem, and allow to employ twitter data for descriptive and predictive 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, renamed T 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. Moreover through a sentiment analysis, we employ the twitters content to estimate graphical models useful in the context of financial systemic risk. To this aim we focus on the Italian bank system and we show how listed banks are connected on the basis of tweets data.

Journal

Quality & QuantitySpringer Journals

Published: Jul 14, 2015

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from
Google Scholar,
PubMed
Create lists to
organize your research
Export lists, citations
Read DeepDyve articles
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off