Konferenzbeitrag

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

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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.

Sprache
Englisch

Erschienen in
In: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019 ; Year: 2019 ; Pages: 67-75 ; Zagreb: IRENET - Society for Advancing Innovation and Research in Economy

Klassifikation
Wirtschaft
Large Data Sets: Modeling and Analysis
Thema
visualization
data science
FinTech
topic modelling
LDA

Ereignis
Geistige Schöpfung
(wer)
Krstić, Živko
Seljan, Sanja
Zoroja, Jovana
Ereignis
Veröffentlichung
(wer)
IRENET - Society for Advancing Innovation and Research in Economy
(wo)
Zagreb
(wann)
2019

Handle
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Original beim Datenpartner anzeigen

Objekttyp

  • Konferenzbeitrag

Beteiligte

  • Krstić, Živko
  • Seljan, Sanja
  • Zoroja, Jovana
  • IRENET - Society for Advancing Innovation and Research in Economy

Entstanden

  • 2019

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