Text Mining and Ruin Theory: A Case Study of Research on Risk Models with Dependence

Renata G. Alcoforado; Alfredo D. Egídio dos Reis

doi:10.57805/revstat.v18i4.313

Text Mining and Ruin Theory

A Case Study of Research on Risk Models with Dependence

Authors

Renata G. Alcoforado Universidade Federal de Pernambuco
Alfredo D. Egídio dos Reis Universidade de Lisboa

DOI:

https://doi.org/10.57805/revstat.v18i4.313

Keywords:

big data, unstructured data, text mining, risk theory, ruin theory, dependence modeling

Abstract

This paper aims to analyze unstructured data using a text mining approach. The work was motivated in order to organize and structure research in Risk Theory. In our study, the subject to be analyzed is composed by 27 published papers of the risk and ruin theory topic, area of actuarial science. They were coded into 32 categories. For the purpose, all data was analyzed and figures were produced using the software NVivo 11 plus. Software NVivo is a specialized tool in analyzing unstructured data, although it is commonly used just for qualitative research. We used it for Quali-Quant analysis.

Downloads

REVSTAT2020v18n4_6

Published

2020-10-20

How to Cite

G. Alcoforado , R., & D. Egídio dos Reis , A. (2020). Text Mining and Ruin Theory: A Case Study of Research on Risk Models with Dependence. REVSTAT-Statistical Journal, 18(4), 483–499. https://doi.org/10.57805/revstat.v18i4.313