Using narbs to create narrative maps from unstructured Big Data: a case study

Ananda Mitra and Sanjay Mamani

International Journal of Logistics Economics and Globalisation, 2014, vol. 6, issue 1, 78-98

Abstract: There is an increasing availability of unstructured textual data in the depositories of big databases that are constantly produced and updated. Such unstructured data, such as status updates on social media, play the role of narrative bits - narbs - in creating specific stories about an individual, group or institution. A selection of narbs emanating from Egypt following the Arab Spring are analysed using the theoretical foundation of the narrative paradigm to demonstrate how analytic protocols adapted from latent semantic analysis and natural language programming can be used to extract narrative categories and maps showing the relationship between the categories which together tell a story based on the narbs scraped and harvested from databases.

Keywords: narbs; narrative bits; Arab Spring; attitude maps; big data; narrative maps; case study; unstructured data; Egypt; latent semantic analysis; natural language programming; NLP; narrative categories. (search for similar items in EconPapers)
Date: 2014
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