Text Mining for Big Data Analysis in Financial Sector: A Literature Review

Mirjana Pejić Bach (), Živko Krstić, Sanja Seljan and Lejla Turulja
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Živko Krstić: Atomic Intelligence, 10000 Zagreb, Croatia
Sanja Seljan: Faculty of Humanities and Social Sciences, Information and Communication Sciences, University of Zagreb, 10000 Zagreb, Croatia
Lejla Turulja: School of Economics and Business, University of Sarajevo, 71000 Sarajevo, Bosna i Hercegovina

Sustainability, 2019, vol. 11, issue 5, 1-27

Abstract: Big data technologies have a strong impact on different industries, starting from the last decade, which continues nowadays, with the tendency to become omnipresent. The financial sector, as most of the other sectors, concentrated their operating activities mostly on structured data investigation. However, with the support of big data technologies, information stored in diverse sources of semi-structured and unstructured data could be harvested. Recent research and practice indicate that such information can be interesting for the decision-making process. Questions about how and to what extent research on data mining in the financial sector has developed and which tools are used for these purposes remains largely unexplored. This study aims to answer three research questions: (i) What is the intellectual core of the field? (ii) Which techniques are used in the financial sector for textual mining, especially in the era of the Internet, big data, and social media? (iii) Which data sources are the most often used for text mining in the financial sector, and for which purposes? In order to answer these questions, a qualitative analysis of literature is carried out using a systematic literature review, citation and co-citation analysis.

Keywords: big data; text mining; financial sector; data science; language (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

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