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

In: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019

Author

Listed:
  • Krstić, Živko
  • Seljan, Sanja
  • Zoroja, Jovana

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.

Suggested Citation

  • Krstić, Živko & Seljan, Sanja & Zoroja, Jovana, 2019. "Visualization of Big Data Text Analytics in Financial Industry: A Case Study of Topic Extraction for Italian Banks," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2019), Rovinj, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019, pages 67-75, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    • Handle: RePEc:zbw:entr19:207665
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    File URL: https://www.econstor.eu/bitstream/10419/207665/1/09-ENT-2019-Krstic-et-al-67-75.pdf
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    Cited by:

    1. Aaryan Gupta & Vinya Dengre & Hamza Abubakar Kheruwala & Manan Shah, 2020. "Comprehensive review of text-mining applications in finance," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-25, December.

    More about this item

    Keywords

    visualization; data science; FinTech; topic modelling; LDA;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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