Earticle

초록

영어

Digital piracy is one of the most significant threats on digital goods, and it’s increasing every year. Many researchers analyze this phenomenon by using and developing different models and approaches, creating an ocean of information. Due to this vast amount of research, it’s crucial to perform a literature analysis to have a global picture and to build an integrity view on digital piracy; however the traditional literature analysis is a tedious process and requires a substantial amount of time. Hence, faster and effective methods are necessary. We performed a non-traditional literature analysis approach using text mining techniques on a collection of 856 digital piracy articles from 29 years across several relevant journals. Therefore, Latent Dirichlet Allocation and igraph were use to group articles on relevant topics and to graph terms associations. This study identified the common trends as well as the relation between the different theories.

목차

Abstract
1. Introduction
2. Methods
2.1 Literature selection
2.2 Text mining and topic modeling
3. Result and analysis
3.1 Term frequency – Word cloud (D1)
3.3 Topics discovery on digital piracy (D2)
3.4 Geographical distribution based on authoraffiliations (D3)
3.5 Map of theories – Network analysis (D4)
4. Conclusions
5. References

키워드

저자

• Lissette Almonte [ Department of Data Science, College of Business Administration, Kookmin University ]
• Byounggu Choi [ College of Business Administration, Kookmin University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국경영정보학회 정기 학술대회 [KMIS Conference]

• 간기

  반년간

• 수록기간

  1990~2025

• 십진분류

  KDC 325 DDC 658