{"title":"衡量智能手机使用情况:调查数据与数字行为数据","authors":"Alexander Wenz, Florian Keusch, Ruben L. Bach","doi":"10.1177/08944393231224540","DOIUrl":null,"url":null,"abstract":"While digital technology use and skills have typically been measured with surveys, digital behavioral data that are passively collected from individuals’ digital devices have recently emerged as an alternative method of measuring technology usage patterns in a more unobtrusive and detailed way. In this paper, we evaluate how passively collected smartphone usage data compare to self-reported measures of smartphone use, considering the three usage dimensions amount of use, variety of use, and activities of use. Based on a sample of smartphone users in Germany who completed a survey and had a tracking app installed on their smartphone, we find that the alignment between the survey and digital behavioral data varies by dimension of smartphone use. Whereas amount of use is considerably overreported in the survey data, variety of use aligns more closely across the two data sources. For activities of use, the alignment differs by type of activity. The results also show that the alignment between survey and digital behavioral data is systematically related to individuals’ sociodemographic characteristics, including age, gender, and educational attainment. Finally, latent class analyses conducted separately for the survey and digital behavioral data suggest similar typologies of smartphone use, although the overlap between the typologies on the individual level is rather small.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"9 4","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring Smartphone Use: Survey Versus Digital Behavioral Data\",\"authors\":\"Alexander Wenz, Florian Keusch, Ruben L. Bach\",\"doi\":\"10.1177/08944393231224540\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While digital technology use and skills have typically been measured with surveys, digital behavioral data that are passively collected from individuals’ digital devices have recently emerged as an alternative method of measuring technology usage patterns in a more unobtrusive and detailed way. In this paper, we evaluate how passively collected smartphone usage data compare to self-reported measures of smartphone use, considering the three usage dimensions amount of use, variety of use, and activities of use. Based on a sample of smartphone users in Germany who completed a survey and had a tracking app installed on their smartphone, we find that the alignment between the survey and digital behavioral data varies by dimension of smartphone use. Whereas amount of use is considerably overreported in the survey data, variety of use aligns more closely across the two data sources. For activities of use, the alignment differs by type of activity. The results also show that the alignment between survey and digital behavioral data is systematically related to individuals’ sociodemographic characteristics, including age, gender, and educational attainment. Finally, latent class analyses conducted separately for the survey and digital behavioral data suggest similar typologies of smartphone use, although the overlap between the typologies on the individual level is rather small.\",\"PeriodicalId\":49509,\"journal\":{\"name\":\"Social Science Computer Review\",\"volume\":\"9 4\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Social Science Computer Review\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1177/08944393231224540\",\"RegionNum\":2,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Science Computer Review","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/08944393231224540","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Measuring Smartphone Use: Survey Versus Digital Behavioral Data
While digital technology use and skills have typically been measured with surveys, digital behavioral data that are passively collected from individuals’ digital devices have recently emerged as an alternative method of measuring technology usage patterns in a more unobtrusive and detailed way. In this paper, we evaluate how passively collected smartphone usage data compare to self-reported measures of smartphone use, considering the three usage dimensions amount of use, variety of use, and activities of use. Based on a sample of smartphone users in Germany who completed a survey and had a tracking app installed on their smartphone, we find that the alignment between the survey and digital behavioral data varies by dimension of smartphone use. Whereas amount of use is considerably overreported in the survey data, variety of use aligns more closely across the two data sources. For activities of use, the alignment differs by type of activity. The results also show that the alignment between survey and digital behavioral data is systematically related to individuals’ sociodemographic characteristics, including age, gender, and educational attainment. Finally, latent class analyses conducted separately for the survey and digital behavioral data suggest similar typologies of smartphone use, although the overlap between the typologies on the individual level is rather small.
期刊介绍:
Unique Scope Social Science Computer Review is an interdisciplinary journal covering social science instructional and research applications of computing, as well as societal impacts of informational technology. Topics included: artificial intelligence, business, computational social science theory, computer-assisted survey research, computer-based qualitative analysis, computer simulation, economic modeling, electronic modeling, electronic publishing, geographic information systems, instrumentation and research tools, public administration, social impacts of computing and telecommunications, software evaluation, world-wide web resources for social scientists. Interdisciplinary Nature Because the Uses and impacts of computing are interdisciplinary, so is Social Science Computer Review. The journal is of direct relevance to scholars and scientists in a wide variety of disciplines. In its pages you''ll find work in the following areas: sociology, anthropology, political science, economics, psychology, computer literacy, computer applications, and methodology.