B1: Digital Trace Data and Mobile Data Collection
The Smartphone Usage Divide: Differences in People's Smartphone Behavior and Implications for Mobile Data Collection
University of Mannheim, Germany
Relevance & Research Question: Researchers increasingly use smartphones for data collection, not only to implement mobile web questionnaires and diaries but also to capture new forms of data from the in-built sensors, such as GPS positioning or acceleration. Existing research on coverage error in these types of studies has distinguished between smartphone owners and non-owners. With increasing smartphone use in the general population, however, the digital divide of the "haves" and "have-nots" has shifted towards inequalities related to the skills and usage patterns of smartphone technology. In this paper, we examine people’s smartphone usage pattern and its implications for the future scope of mobile data collection.
Methods & Data: We collected survey data from six samples of smartphone owners in Germany and Austria between 2016 and 2020 (three probability samples: n1=3,956; n2=2,186; n3=632; three nonprobability samples: n4=2,623; n5=2,525; n6=1,214). Respondents were asked about their frequency of smartphone use, their level of smartphone skills, and the activities that they carry out on their smartphone. To identify different types of smartphone users, we conduct a latent class analysis (LCA), which classifies individuals based on their similarity in smartphone usage patterns.
Results: First, we will assess which smartphone usage types can be identified in the samples of smartphone owners. Second, we will examine whether the different smartphone usage types vary systematically by socio-demographic characteristics, privacy concerns towards research activities on a smartphone, and key survey variables. Third, we will investigate how the composition of the smartphone usage types change over time.
Added Value: Smartphone-based studies, even those relying on passive data collection, require participants to be able to engage with their device, such as downloading an app or activating location tracking. Therefore, researchers not only need to understand which subgroups of the population have access to smartphone technology but also how people are able to use the technology. By studying smartphone usage patterns among smartphone owners in Germany and Austria, this paper provides initial empirical evidence on this important issue.
Digital trace data collection through data donation
Utrecht University, Netherlands, The
Relevance and Research Question
Digital traces left by citizens during the course of life hold an enormous potential for social-scientific discoveries, because they measure aspects of social life that are difficult to measure by traditional means. Typically, digital traces are collected through APIs and web scraping. This is however not always suitable for social-scientific research questions. Disadvantages are that the data cannot be used for questions on individual level, only public data is provided, the data pertain to a non-random subset of the platform’s users and users who generate the data cannot be contacted for their consent. We aim to develop an alternative workflow that overcomes these issues.
We propose a workflow that analyses digital traces by using data download packages (DDPs). As of May 2018, any entity that processes the personal data of citizens of the European Union is legally obligated by the GDPR to provide that data to the data subject upon request in digital format. Most major private data processing entities, comprising social media platforms, smartphone systems, search engines, photo storage, e-mail, banks, energy providers, and online shops comply with this right.
Our proposed workflow consists of five steps. First, data subjects are recruited as respondents using standard survey sampling techniques. Next, respondents request their DDPs with various providers, storing these locally on their own device. Stored DDPs are then locally processed to extract relevant research variables, after which consent is requested of the respondent to send these derived variables to the researcher for analysis.
Results and added value
We will present a proof-of-concept of developed software that enables the proposed workflow together with some use-cases. By using the workflow and the developed software, researchers can answer research questions with digital trace data while overcoming the current measurement issues and issues with informed consent.
Smartphone behavior during the Corona pandemic – How Germans used apps in 2020.
1Murmuras, Germany; 2University of Bonn, Germany; 3University of Amsterdam, Netherlands; 4Philipps University of Marburg, Germany
The year 2020 changed dramatically our everyday routines. With Corona pandemic-related social distancing measures, connecting virtually helped us cope with isolation. While no single tool provides a whole picture of these changes, smartphones capture a significant part of online behavior. We looked at the usage of top smartphone apps to answer the following research questions:
What were the most popular smartphone apps in 2020?
How did they differ by demographics groups and occupations?
How did they change over the year?
Were these changes COVID-19 related?
Methods & Data:
Our academic partners recruited 1070 Participants from Germany for scientific purposes. We collected their real-time app usage data via the Murmuras app with the fully GDPR-conform consent and conducted exploratory data analysis.
Our participants spent on average almost 4 hours using their smartphones. The top five apps - WhatsApp, Instagram, YouTube, Chrome, and Facebook are popular throughout all demographics. Together they constitute almost 50% of all usage we recorded. Three of them - WhatsApp, Instagram, and Facebook capture most of our online social and communication behavior. WhatsApp remains at the top for all demographics groups. Instagram is used longer by women, younger people, and students. Facebook is still the second most used app for people above 30 and employed people.
Phone usage increased significantly in March and April, marked by a large number of COVID-19 cases and strict lockdown. Usage of social and communication apps in these months increased by over 20%. Time spent in entertainment and media apps showed a slight decrease in March and a rapid increase in the following months. Interestingly with the second wave of the pandemic in Autumn, we see an increase in media and social categories but no changes in communication apps.
With the use of real data, our study brings a better understanding of online behavior in the year 2020, when compared to questionnaires and app store-based studies. We look into demographic and occupational differences as well as changes throughout the year and the influence of lockdowns. This new perspective provides insight into changes in our habits brought by the COVID-19 pandemic.