Tracking Phantastic Objects: A Computer Algorithmic Investigation of Narrative Evolution in Unstructured Data Sources
David Tuckett, Robert Elliot Smith, Rickard Nyman, Tracking phantastic objects: A computer algorithmic investigation of narrative evolution in unstructured data sources, Social Networks, Volume 38, July 2014, Pages 121-133, ISSN 0378-8733
Posted: 7 Mar 2014 Last revised: 7 Dec 2015
Date Written: February 1, 2014
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.
Keywords: Narrative, Sentiment Analysis, Phantastic Object, Networks, Financial Markets
JEL Classification: B40, C15, C82, G12
Suggested Citation: Suggested Citation