Prediction of the mobile game players’ payments-related retention from the Big Data perspective

• Autorzy: Bilski Piotr , Łabędzki Rafał , Bilski Adrian

Identyfikatory

DOI

10.24425/ijet.2024.152510

• Języki publikacji: EN

Abstrakty

EN

The paper presents the methodology for evaluating mobile game players retention, which is the basis for generating economic income for its creators. The system for collecting and processing the in-game data (events related to the players’ actions) exploiting the Big Data cloud platform is described. The player profile with the crucial features allowing for the retention analysis is introduced. Datasets generated for the My Spa Resort mobile game by CherryPick company are described. The retention prediction approach based on the similarity estimation between the analyzed and already inactive players is presented. Results of the prediction using the k Nearest Neighbors (kNN) classifier are discussed.

Słowa kluczowe

EN

retention; data science; prediction; mobile game

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2024
• Tom: Vol. 70, No. 4
• Strony: 1081--1087
• Opis fizyczny: Bibliogr., 18 poz., rys., tab.

Twórcy

autor

Bilski Piotr

• Warsaw University of Technology, Poland

• https://orcid.org/0000-0002-5463-9411

autor

Łabędzki Rafał

• Warsaw School of Economics

autor

Bilski Adrian

• Warsaw University of Life Sciences

Bibliografia

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Uwagi

1. Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).

2. This work was supported by National Centre of Research and Development, project number POIR.01.01.01-00-0927/17, acronym “Cherrylytics.”