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Text Mining for Big Data Analysis in Financial Sector: A Literature Review

Author

Listed:
  • Mirjana Pejić Bach

    (Faculty of Economics & Business, University of Zagreb, 10000 Zagreb, Croatia)

  • Živko Krstić

    (Atomic Intelligence, 10000 Zagreb, Croatia)

  • Sanja Seljan

    (Faculty of Humanities and Social Sciences, Information and Communication Sciences, University of Zagreb, 10000 Zagreb, Croatia)

  • Lejla Turulja

    (School of Economics and Business, University of Sarajevo, 71000 Sarajevo, Bosna i Hercegovina)

Abstract

Big data technologies have a strong impact on different industries, starting from the last decade, which continues nowadays, with the tendency to become omnipresent. The financial sector, as most of the other sectors, concentrated their operating activities mostly on structured data investigation. However, with the support of big data technologies, information stored in diverse sources of semi-structured and unstructured data could be harvested. Recent research and practice indicate that such information can be interesting for the decision-making process. Questions about how and to what extent research on data mining in the financial sector has developed and which tools are used for these purposes remains largely unexplored. This study aims to answer three research questions: (i) What is the intellectual core of the field? (ii) Which techniques are used in the financial sector for textual mining, especially in the era of the Internet, big data, and social media? (iii) Which data sources are the most often used for text mining in the financial sector, and for which purposes? In order to answer these questions, a qualitative analysis of literature is carried out using a systematic literature review, citation and co-citation analysis.

Suggested Citation

  • Mirjana Pejić Bach & Živko Krstić & Sanja Seljan & Lejla Turulja, 2019. "Text Mining for Big Data Analysis in Financial Sector: A Literature Review," Sustainability, MDPI, vol. 11(5), pages 1-27, February.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:5:p:1277-:d:209769
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Polak, Marija & Kolić Stanić, Matilda & Togonal, Marijana, 2022. "Artificial Intelligence in Communication with Music Fans: An Example from South Korea," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2022), Hybrid Conference, Opatija, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Hybrid Conference, Opatija, Croatia, 17-18 June 2022, pages 48-63, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    2. Osmud Rahman & Dingtao Hu & Benjamin C. M. Fung, 2023. "A Systematic Literature Review of Fashion, Sustainability, and Consumption Using a Mixed Methods Approach," Sustainability, MDPI, vol. 15(16), pages 1-37, August.
    3. 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.
    4. Chunting Liu & Shanshan Wang & Guozhu Jia, 2020. "Exploring E-Commerce Big Data and Customer-Perceived Value: An Empirical Study on Chinese Online Customers," Sustainability, MDPI, vol. 12(20), pages 1-22, October.
    5. Gang-Hoon Seo & Munehiko Itoh, 2020. "Perceptions of Customers as Sustained Competitive Advantages of Global Marketing Airline Alliances: A Hybrid Text Mining Approach," Sustainability, MDPI, vol. 12(15), pages 1-15, August.
    6. Nguyen Bang & Nguyen Van-Ho & Ho Thanh, 2021. "Sentiment Analysis of Customer Feedback in Online Food Ordering Services," Business Systems Research, Sciendo, vol. 12(2), pages 46-59, December.
    7. Alexander Musaev & Andrey Makshanov & Dmitry Grigoriev, 2022. "Numerical Studies of Channel Management Strategies for Nonstationary Immersion Environments: EURUSD Case Study," Mathematics, MDPI, vol. 10(9), pages 1-20, April.
    8. Yuegang Song & Ruibing Wu, 2022. "The Impact of Financial Enterprises’ Excessive Financialization Risk Assessment for Risk Control based on Data Mining and Machine Learning," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1245-1267, December.
    9. Vasja Roblek & Maja Meško & Mirjana Pejić Bach & Oshane Thorpe & Polona Šprajc, 2020. "The Interaction between Internet, Sustainable Development, and Emergence of Society 5.0," Data, MDPI, vol. 5(3), pages 1-27, September.
    10. Seo Gang-Hoon, 2020. "A Content Analysis of International Airline Alliances Mission Statements," Business Systems Research, Sciendo, vol. 11(1), pages 89-105, March.
    11. Rybinski, Krzysztof, 2021. "Ranking professional forecasters by the predictive power of their narratives," International Journal of Forecasting, Elsevier, vol. 37(1), pages 186-204.
    12. Fernando Zambrano Farias & María del Carmen Valls Martínez & Pedro Antonio Martín-Cervantes, 2021. "Explanatory Factors of Business Failure: Literature Review and Global Trends," Sustainability, MDPI, vol. 13(18), pages 1-26, September.
    13. Christopher Gerling & Stefan Lessmann, 2023. "Multimodal Document Analytics for Banking Process Automation," Papers 2307.11845, arXiv.org, revised Nov 2023.
    14. Rybinski, Krzysztof, 2020. "The forecasting power of the multi-language narrative of sell-side research: A machine learning evaluation," Finance Research Letters, Elsevier, vol. 34(C).
    15. Ćurlin Tamara & Jaković Božidar & Miloloža Ivan, 2019. "Twitter usage in Tourism: Literature Review," Business Systems Research, Sciendo, vol. 10(1), pages 102-119, April.
    16. Seo Gang-Hoon & Itoh Munehiko & Li Zhonghui, 2021. "Strategic Communication and Competitive Advantage: Assessing CEO Letters of Global Airline Alliances," Foundations of Management, Sciendo, vol. 13(1), pages 57-72, January.
    17. Cristina Ortega-Rodríguez & Ana Licerán-Gutiérrez & Antonio Luis Moreno-Albarracín, 2020. "Transparency as a Key Element in Accountability in Non-Profit Organizations: A Systematic Literature Review," Sustainability, MDPI, vol. 12(14), pages 1-22, July.
    18. Berkin, Anil & Aerts, Walter & Van Caneghem, Tom, 2023. "Feasibility analysis of machine learning for performance-related attributional statements," International Journal of Accounting Information Systems, Elsevier, vol. 48(C).
    19. Carlos Arcila-Calderón & David Blanco-Herrero & Maximiliano Frías-Vázquez & Francisco Seoane-Pérez, 2021. "Refugees Welcome? Online Hate Speech and Sentiments in Twitter in Spain during the Reception of the Boat Aquarius," Sustainability, MDPI, vol. 13(5), pages 1-16, March.
    20. Senave, Elseline & Jans, Mieke J. & Srivastava, Rajendra P., 2023. "The application of text mining in accounting," International Journal of Accounting Information Systems, Elsevier, vol. 50(C).
    21. Vasja Roblek & Oshane Thorpe & Mirjana Pejic Bach & Andrej Jerman & Maja Meško, 2020. "The Fourth Industrial Revolution and the Sustainability Practices: A Comparative Automated Content Analysis Approach of Theory and Practice," Sustainability, MDPI, vol. 12(20), pages 1-27, October.
    22. Rongjiang Cai & Tao Lv & Xu Deng, 2021. "Evaluation of Environmental Information Disclosure of Listed Companies in China’s Heavy Pollution Industries: A Text Mining-Based Methodology," Sustainability, MDPI, vol. 13(10), pages 1-23, May.
    23. Vrdoljak Ivana, 2023. "Lifelong Education in Economics, Business and Management Research: Literature Review," Business Systems Research, Sciendo, vol. 14(1), pages 153-172, September.

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