Utilizing Players' Playtime Records for Churn Prediction: Mining Playtime Regularity

12/15/2019
by   Wanshan Yang, et al.
0

In the free online game industry, churn prediction is an important research topic. Reducing the churn rate of a game significantly helps with the success of the game. Churn prediction helps a game operator identify possible churning players and keep them engaged in the game via appropriate operational strategies, marketing strategies, and/or incentives. Playtime related features are some of the widely used universal features for most churn prediction models. In this paper, we consider developing new universal features for churn predictions for long-term players based on players' playtime.

READ FULL TEXT
research
12/15/2019

Utilizing Players' In-game Time Spending Records for Churn Prediction: Mining In-game Time Spending Regularity

In the free online game industry, churn prediction is an important resea...
research
11/26/2020

Understand Watchdogs: Discover How Game Bot Get Discovered

The game industry has long been troubled by malicious activities utilizi...
research
08/24/2023

Out of the Box Thinking: Improving Customer Lifetime Value Modelling via Expert Routing and Game Whale Detection

Customer lifetime value (LTV) prediction is essential for mobile game pu...
research
01/04/2018

Hats: all or nothing

N distinguishable players are randomly fitted with a white or black hat,...
research
02/05/2020

Stimulating Creativity with FunLines: A Case Study of Humor Generation in Headlines

Building datasets of creative text, such as humor, is quite challenging....
research
07/05/2022

Putting the Con in Context: Identifying Deceptive Actors in the Game of Mafia

While neural networks demonstrate a remarkable ability to model linguist...
research
03/15/2012

Learning Game Representations from Data Using Rationality Constraints

While game theory is widely used to model strategic interactions, a natu...

Please sign up or login with your details

Forgot password? Click here to reset