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

Authors: Ananda Mitra; Sanjay Mamani

Addresses: Department of Communication, Box 7347 Reynolda Station, Winston-Salem, NC 27109, USA ' 4537 Stimpson Ridge Dr., Pfafftown, NC 27040, USA

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.

DOI: 10.1504/IJLEG.2014.064283

International Journal of Logistics Economics and Globalisation, 2014 Vol.6 No.1, pp.78 - 98

Received: 04 Sep 2013
Accepted: 26 Oct 2013

Published online: 14 Aug 2014 *

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