Tracking phantastic objects: A computer algorithmic investigation of narrative evolution in unstructured data sources |
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| Affiliation: | 1. UCL Centre for the Study of Decision-Making Uncertainty, Faculty of Brain Sciences, University College London, United Kingdom;2. Institute of Psychoanalysis, London, United Kingdom;3. Financial Computing Group, Department of Computer Science, University College London, United Kingdom;4. Department of Computer Science, University College London, United Kingdom;1. Sandia National Laboratories, Livermore, CA, United States;2. Idaho National Laboratory, Idaho Falls, ID, United States;3. Sandia National Laboratories, Albuquerque, NM, United States |
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| 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. |
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| Keywords: | Narrative Sentiment analysis Phantastic object Networks Financial markets |
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