{"title":"用主观用户体验数据预测元得分","authors":"Jari Takatalo, J. Häkkinen","doi":"10.1145/2658537.2661299","DOIUrl":null,"url":null,"abstract":"The aim of this study is to test how well a subjective user experience (UX) data predicts the Metascore of a digital game. The Metascore calculated by the Metacritic.com is one of the most important indicators of a game's commercial success. Thus, game companies are interested in finding reliable in-house tools to estimate the Metascore before releasing their product. We utilized subjective survey data to test a preliminary regression model for Metascore. The model explained over 50% of the variance between the Metascores. Practically, this means that we can predict a correct Metascore class (e.g., universal acclaim) with 75% accuracy. These promising results provide good grounds for future research on the topic.","PeriodicalId":126882,"journal":{"name":"Proceedings of the first ACM SIGCHI annual symposium on Computer-human interaction in play","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting the metascore with a subjective user experience data\",\"authors\":\"Jari Takatalo, J. Häkkinen\",\"doi\":\"10.1145/2658537.2661299\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this study is to test how well a subjective user experience (UX) data predicts the Metascore of a digital game. The Metascore calculated by the Metacritic.com is one of the most important indicators of a game's commercial success. Thus, game companies are interested in finding reliable in-house tools to estimate the Metascore before releasing their product. We utilized subjective survey data to test a preliminary regression model for Metascore. The model explained over 50% of the variance between the Metascores. Practically, this means that we can predict a correct Metascore class (e.g., universal acclaim) with 75% accuracy. These promising results provide good grounds for future research on the topic.\",\"PeriodicalId\":126882,\"journal\":{\"name\":\"Proceedings of the first ACM SIGCHI annual symposium on Computer-human interaction in play\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the first ACM SIGCHI annual symposium on Computer-human interaction in play\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2658537.2661299\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the first ACM SIGCHI annual symposium on Computer-human interaction in play","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2658537.2661299","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predicting the metascore with a subjective user experience data
The aim of this study is to test how well a subjective user experience (UX) data predicts the Metascore of a digital game. The Metascore calculated by the Metacritic.com is one of the most important indicators of a game's commercial success. Thus, game companies are interested in finding reliable in-house tools to estimate the Metascore before releasing their product. We utilized subjective survey data to test a preliminary regression model for Metascore. The model explained over 50% of the variance between the Metascores. Practically, this means that we can predict a correct Metascore class (e.g., universal acclaim) with 75% accuracy. These promising results provide good grounds for future research on the topic.