Visualization of big data text analytics in financial industry: a case study of topic extraction for Italian banks (CROSBI ID 683083)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Krstić, Živko ; Seljan, Sanja ; Zoroja, Jovana
engleski
Visualization of big data text analytics in financial industry: a case study of topic extraction for Italian banks
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.
visualization, data science, FinTech, topic modelling, LDA
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Podaci o prilogu
67-75.
2019.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the ENTRENOVA '19 - ENTreprise REsearch InNOVAtion Conference
Milković, Marin ; Seljan, Sanja ; Pejić Bach, Mirjana ; Peković, Sanja ; Perovic, Djurdjica
Zagreb: Irenet
1849-7950
Podaci o skupu
ENTerprise REsearch InNOVAtion (ENTRENOVA) Conference 2019
predavanje
12.09.2019-14.09.2019
Rovinj, Hrvatska