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Pregled bibliografske jedinice broj: 1029981

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


Krstić, Živko; Seljan, Sanja; Zoroja, Jovana
Visualization of Big Data Text Analytics in Financial Industry: A Case Study of Topic Extraction for Italian Banks // Proceedings of the ENTRENOVA '19 - ENTreprise REsearch InNOVAtion Conference / Milković, Marin ; Seljan, Sanja ; Pejić Bach, Mirjana ; Peković, Sanja ; Perovic, Djurdjica (ur.).
Zagreb: Irenet, 2019. str. 67-75 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 1029981 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

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

Autori
Krstić, Živko ; Seljan, Sanja ; Zoroja, Jovana

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the ENTRENOVA '19 - ENTreprise REsearch InNOVAtion Conference / Milković, Marin ; Seljan, Sanja ; Pejić Bach, Mirjana ; Peković, Sanja ; Perovic, Djurdjica - Zagreb : Irenet, 2019, 67-75

Skup
ENTRENOVA - ENTerprise REsearch InNOVAtion Conference

Mjesto i datum
Rovinj, Hrvatska, 10-12.09.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
visualization, data science, FinTech, topic modelling, LDA

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Ekonomija, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Projekt / tema
43-922-1011

Ustanove
Ekonomski fakultet, Zagreb,
Filozofski fakultet, Zagreb

Profili:

Avatar Url Sanja Seljan (autor)

Avatar Url Jovana Zoroja (autor)

Citiraj ovu publikaciju

Krstić, Živko; Seljan, Sanja; Zoroja, Jovana
Visualization of Big Data Text Analytics in Financial Industry: A Case Study of Topic Extraction for Italian Banks // Proceedings of the ENTRENOVA '19 - ENTreprise REsearch InNOVAtion Conference / Milković, Marin ; Seljan, Sanja ; Pejić Bach, Mirjana ; Peković, Sanja ; Perovic, Djurdjica (ur.).
Zagreb: Irenet, 2019. str. 67-75 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Krstić, Ž., Seljan, S. & Zoroja, J. (2019) Visualization of Big Data Text Analytics in Financial Industry: A Case Study of Topic Extraction for Italian Banks. U: Milković, M., Seljan, S., Pejić Bach, M., Peković, S. & Perovic, D. (ur.)Proceedings of the ENTRENOVA '19 - ENTreprise REsearch InNOVAtion Conference.
@article{article, year = {2019}, pages = {67-75}, keywords = {visualization, data science, FinTech, topic modelling, LDA}, title = {Visualization of Big Data Text Analytics in Financial Industry: A Case Study of Topic Extraction for Italian Banks}, keyword = {visualization, data science, FinTech, topic modelling, LDA}, publisher = {Irenet}, publisherplace = {Rovinj, Hrvatska} }




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