Tracking phantastic objects: A computer algorithmic investigation of narrative evolution in unstructured data sources

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.