{"title":"基于机器学习的民族认同影响因素研究","authors":"宇拓 王","doi":"10.12677/isl.2023.71004","DOIUrl":null,"url":null,"abstract":"Based on the 2019 Chinese Social Survey (CSS 2019), this research explores the influencing factors of national identity. After data preprocessing, we use the 266 variables to build an MLP model to predict the national identity of the subjects and use the DALEX package to select the most valuable predictor. In general, the predictive factors determined by the machine learning model are consistent with results of prior studies, such as economic factors, religion, social security, etc. This research supplements previous studies on the factors affecting national identity, and provides data support","PeriodicalId":69869,"journal":{"name":"交叉科学快报","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on the Influencing Factors of National Identity Based on Machine Learning\",\"authors\":\"宇拓 王\",\"doi\":\"10.12677/isl.2023.71004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the 2019 Chinese Social Survey (CSS 2019), this research explores the influencing factors of national identity. After data preprocessing, we use the 266 variables to build an MLP model to predict the national identity of the subjects and use the DALEX package to select the most valuable predictor. In general, the predictive factors determined by the machine learning model are consistent with results of prior studies, such as economic factors, religion, social security, etc. This research supplements previous studies on the factors affecting national identity, and provides data support\",\"PeriodicalId\":69869,\"journal\":{\"name\":\"交叉科学快报\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"交叉科学快报\",\"FirstCategoryId\":\"1089\",\"ListUrlMain\":\"https://doi.org/10.12677/isl.2023.71004\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"交叉科学快报","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.12677/isl.2023.71004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on the Influencing Factors of National Identity Based on Machine Learning
Based on the 2019 Chinese Social Survey (CSS 2019), this research explores the influencing factors of national identity. After data preprocessing, we use the 266 variables to build an MLP model to predict the national identity of the subjects and use the DALEX package to select the most valuable predictor. In general, the predictive factors determined by the machine learning model are consistent with results of prior studies, such as economic factors, religion, social security, etc. This research supplements previous studies on the factors affecting national identity, and provides data support