Abstract

http://ssrn.com/abstract=2405447
 


 



Tracking Phantastic Objects: A Computer Algorithmic Investigation of Narrative Evolution in Unstructured Data Sources


David Tuckett


University College London (UCL)

Robert Elliot Smith


University College London

Rickard Nyman


University College London

February 1, 2014


Abstract:     
We develop social network and "relative sentiment shift" analysis techniques to study how financial narratives influence financial markets. First, we analyze Reuters News articles focusing on narratives about Fannie Mae. Second, we analyze Broadband and Energy narratives in the Enron Corporation email database. Combining datasets we show that phantastic object narratives can be detected and tracked as they develop and spread through networks to lead to a disconnect between narrative and underlying "reality". The methods may be applicable to other text datasets to create early warnings.

Number of Pages in PDF File: 39

Keywords: Narrative, Sentiment Analysis, Phantastic Object, Networks, Financial Markets

JEL Classification: B40, C15, C82, G12

working papers series


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Date posted: March 7, 2014  

Suggested Citation

Tuckett, David and Smith, Robert Elliot and Nyman, Rickard, Tracking Phantastic Objects: A Computer Algorithmic Investigation of Narrative Evolution in Unstructured Data Sources (February 1, 2014). Available at SSRN: http://ssrn.com/abstract=2405447 or http://dx.doi.org/10.2139/ssrn.2405447

Contact Information

David Tuckett (Contact Author)
University College London (UCL) ( email )
Gower Street
London, WC1E 7HU
United Kingdom
HOME PAGE: http://www.ucl.ac.uk/psychoanalysis/unit-staff/david.htm
Robert Elliot Smith
University College London ( email )
Gower Street
London, WC1E 6BT
United Kingdom
Rickard Nyman
University College London ( email )
Gower Street
London, WC1E 6BT
United Kingdom
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