{'fraction_non_alphanumeric': 0.025044722719141325, 'fraction_numerical': 0.0, 'mean_word_length': 5.363636363636363, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Vector-based Churn Prediction using Neural Networks in Mobile Games

Due to revenue contribution, increasing churn prediction’s accuracy in mobile games is a significant research to maintain user’s retention. Many existing studies have focused on predicting whether game users churn, but this paper predicts churn-vector in mobile games. The advantages of churn-vector are twofold – increasing the accuracy of churn prediction and helping promotion campaign to minimize user attrition. This paper compared six prediction algorithms with churn-vector and -day.