Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
Session Overview
Session
B09: Using Smartphone Data for Social Science Research
Time:
Friday, 08/Mar/2019:
12:00 - 1:00

Session Chair: Anne Elevelt, Utrecht University, Netherlands, The
Location: Room 158
TH Köln – University of Applied Sciences

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Presentations

Process Quality and Adherence in a Mobile App Study to Collect Expenditure Data within a Probability Household Longitudinal Study

Carli Lessof1, Annette Jäckle2, Mick Couper3, Thomas F Crossley2

1Southampton University, United Kingdom; 2University of Essex, United Kingdom; 3University of Michigan, United States

Relevance and Research Question

Spending is hard to measure accurately; respondents may not recall all purchases, they may telescope events and may struggle to estimate totals. Paper-based expenditure diaries are designed to improve reporting accuracy but are burdensome and reported purchases decline over time. In this paper we explore whether data quality is improved using a mobile app which participants use to scan receipts, enter purchases manually or record ‘no spend’ days for a month. We address three research questions:

• To what extent do participants adhere to the spending study protocol?

• Which respondent characteristics and behaviors are related to adherence?

• Does adherence change over the month period?

Methods and Data

The analysis is based on a supplementary study designed to measure household expenditure as part of a nationally representative household panel survey. We invited 2,432 members of the UK Household Longitudinal Study Innovation Panel to download an app and report all their spending on goods and services for a month. Fieldwork took place from late 2016 to early 2017. The paper is based on 268 participants, using data from mobile app entries, scanned receipts, app paradata and covariates from prior study waves and an app registration survey.

Results

We present levels of adherence based on four outcome measures: daily app use, number of purchases reported, proportion of purchases reported by scanning a receipt (rather than entering summary information) and elapsed time between making a purchase and scanning a receipt. We present separate mixed effect multilevel models for each outcome, identifying the key predictors associated with adherence. We model time to examine change in adherence over the study month. Finally, we examine the relationship between the four measures of adherence.

Added Value

This paper recognizes the complexity of full participation in mobile app studies which involve multiple tasks over an extended period. We look beyond initial participation and define and operationalize the more multi-faceted concept of adherence. Our findings will advance conceptualization and implementation of mobile app studies, resulting in better data quality and will ultimately help realize the potential that new technologies offer data collectors.


Lessof-Process Quality and Adherence in a Mobile App Study-180.pdf

The Appiness project - How do (un)happy people behave online?

François Erner

respondi, France

Relevance & Research Question

The Internet has been hailed as a revolutionary tool for bringing people together; sharing knowledge and engaging audiences. But there have also been claims that the Internet has become addictive, increased social isolation and helped to spread hate.

With all that in mind, our objective was to find out if connected technologies are, overall, beneficial or detrimental to our well-being and how.

Over the past decade, measuring and tracking population happiness has become an increasingly important priority for country leaders around the world. The World Happiness Report, supported by the UN, measures well-being all around the world. However, these surveys do not include in-depth analysis about the impact of the digital world on general well-being.

Methods & Data

We conducted this research in order to be able to cross analyse the results of these happiness indexes with online behaviour. Our research - in France, Germany and the UK - combined a traditional online survey, which matched the happiness question wording to the official well-being surveys, with passive tracking data (i.e. web and app behaviour tracked across participant’s phones, tablets and PC/laptops). To obtain real behavioural data was vital here, because when it comes to Internet usage, declarative data may be biased or inaccurate.

Results & Added Value

So what did we find? The key finding was that, as a general rule, the more time you spend on the internet, the less happy you are. This finding was consistent in each of the three countries where we conducted the research.

We also found some fascinating insights when we analysed the happiness of people using particular websites/apps. We are able to depict a cartography of the internet in terms of the happiness score of the audience: the happy and the unhappy zones of the internet.

We are as such able to relate the internet usage by a certain segment of the population to topical issues like “internet addiction”, “social media consumption”, “fake news”… We will also demonstrate/illustrate how this research could be insightful for the market research industry itself.


Erner-The Appiness project-143.pptx

Enriching an Ongoing Panel Survey with Mobile Phone Measures: The IAB-SMART App

Georg-Christoph Haas1,2, Frauke Kreuter1,2,4, Sebastian Bähr1, Florian Keusch2, Mark Trappmann1,3

1Institute for Employment Research; 2University of Mannheim; 3University of Bamberg; 4University of Maryland

The panel study “Labour market and social security” (PASS) is a major data source for labor market and poverty research in Germany with annual interviews since 2007. In January 2018, the supplemental IAB-SMART study has been started, in which selected PASS-participants were asked to install a research app on their smartphones. The IAB-SMART app combines short questionnaires that can be triggered by geographic location with passive data collection on a variety of measures (e.g. geographic location, app use). The triggering of questions allows us to enrich annual retrospective information with data collected immediately after a certain event (e.g. a visit to the local job center). Passive data collection allows innovative measures, e.g. for the integration into social networks via phone and text message logs that complement traditional survey measures. Furthermore, the additional smartphone measures create the potential to address new research questions related to the labor market and technology use (digital stress, home office performance). Finally, the study provides new insights in the day structure and coping behavior of unemployed persons and thus replicate aspects of the classic Marienthal case study from the 1930s with modern means. In this presentation, we will provide an overview of the study and share our experiences in conducting an app project. We will focus on data protection issues, implementation of the fieldwork, participation in the study and participation in short surveys.



 
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