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Visualization of Big Data Text Analytics in Financial Industry: A Case Study of Topic Extraction for Italian Banks

Živko Krstić orcid.org/0000-0003-0767-7658 ; Atomic Intelligence, Data Science Department, Zagreb, Croatia
Sanja Seljan orcid.org/0000-0001-9048-419X ; Faculty of Humanities and Social Sciences, Information and Communication Sciences, Zagreb, Croatia
Jovana Zoroja orcid.org/0000-0003-2178-2913 ; Faculty of Economics and Business, Zagreb, Croatia

Abstract

Textual data and analysis can derive new insights and bring valuable business insights. These insights can be further leveraged by making better future business decisions. Sources that are used for text analysis in financial industry vary from internal word documents, email to external sources like social media, websites or open data. The system described in this paper will utilize data from social media (Twitter) and tweets related to Italian banks, in Italian. This system is based on open source tools (R language) and topic extraction model was created to gather valuable information. This paper describes methods used for data ingestion, modelling, visualizations of results and insights.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Keywords

Hrčak ID:

250995

URI

https://hrcak.srce.hr/250995

Publication date:

31.10.2019.

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