使用多特征多方法模型估算数字痕迹数据和调查的测量质量

IF 3 2区社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Social Science Computer Review Pub Date : 2024-05-22 DOI:10.1177/08944393241254464

Alexandru Cernat, Florian Keusch, Ruben L. Bach, Paulina K. Pankowska

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引用次数: 0

摘要

数字跟踪数据作为一种捕捉人类行为的潜在方式，正受到越来越多的关注。然而，这类数据远非完美，与传统的社会调查相比，可能并不总能提供更好的数据。在本研究中，我们采用多特质多方法（MTMM）模型对智能手机使用调查和数字追踪数据的测量质量进行了评估。实验设计包括用五种方法测量与智能手机使用相关的五个主题（特质）：三种不同的调查量表（一个 5 分和 7 分频率量表以及一个关于持续时间的开放式问题）和来自数字追踪数据的两种测量方法（频率和持续时间）。我们的研究表明，调查和数字跟踪数据测量之间的相关性非常低。我们还表明，所有测量方法都远非完美，虽然与调查相比，数字跟踪数据的质量似乎更高，但事实并非总是如此。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Estimating Measurement Quality in Digital Trace Data and Surveys Using the MultiTrait MultiMethod Model

Digital trace data are receiving increased attention as a potential way to capture human behavior. Nevertheless, this type of data is far from perfect and may not always provide better data compared to traditional social surveys. In this study we estimate measurement quality of survey and digital trace data on smartphone usage with a MultiTrait MultiMethod (MTMM) model. The experimental design included five topics relating to the use of smartphones (traits) measured with five methods: three different survey scales (a 5- and a 7-point frequency scale and an open-ended question on duration) and two measures from digital trace data (frequency and duration). We show that surveys and digital trace data measures have very low correlation with each other. We also show that all measures are far from perfect and, while digital trace data appears to have often better quality compared to surveys, that is not always the case.

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来源期刊

Social Science Computer Review 社会科学-计算机：跨学科应用

CiteScore

9.00

自引率

4.90%

发文量

审稿时长

>12 weeks

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.