Integration research 2.0
Harnessing the power of new data sources to advance knowledge on behavior and attitudes of migrants and natives
For decades, social scientists have relied on self-reported data from surveys to study integration efforts of refugees and migrants as well as natives’ attitudes on immigrants and immigration policies. Together with administrative records (e.g., from asylum registration centers, welfare agencies, and employment offices), these data are an important resource for decision-makers on every federal level to manage integration tasks and design integration policies. However, the collection of these data can be slow and expensive, and they are susceptible to social desirable reporting. As a consequence, the resulting findings are often only available after an extended period of time and potentially biased. To overcome these issues, we study three new forms of data and novel approaches to data collection that promise faster, more frequent, and potentially also more accurate information for social science research in general and studies on immigration and integration in particular: (1) passively collected data from smartphone sensors and apps , (2) aggregated Internet search queries, and (3) responses obtained from voting advice applications. Each of these approaches has its own limitations, but they could make significant contributions through complementing traditional data collection and overcoming some of its shortcomings.
Our work program consists of three work packages, in which we first assess the feasibility and quality of each new data source proposed. More specifically, we address questions of technical availability, the quality of the new data compared to information obtained from relevant traditional sources, and general feasibility issues that will be relevant to future research in this area. In a second step, we plan to conduct specific case studies within the context of integration in Germany to illustrate how each new data source and data collection method can be implemented and how it may contribute to answering integration-related research questions.
The results from this project will inform methodological best practices in using these new data sources as supplements to traditional ones, especially when examining integration-related topics. The findings will thus help advance the field of integration research and the social sciences in general by adapting new technological possibilities that will enable researchers to answer existing research questions better and to investigate completely new issues.
Collaborators: Christoph Sajons
Funding: Fritz Thyssen Foundation
Related publications:
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Our work program consists of three work packages, in which we first assess the feasibility and quality of each new data source proposed. More specifically, we address questions of technical availability, the quality of the new data compared to information obtained from relevant traditional sources, and general feasibility issues that will be relevant to future research in this area. In a second step, we plan to conduct specific case studies within the context of integration in Germany to illustrate how each new data source and data collection method can be implemented and how it may contribute to answering integration-related research questions.
The results from this project will inform methodological best practices in using these new data sources as supplements to traditional ones, especially when examining integration-related topics. The findings will thus help advance the field of integration research and the social sciences in general by adapting new technological possibilities that will enable researchers to answer existing research questions better and to investigate completely new issues.
Collaborators: Christoph Sajons
Funding: Fritz Thyssen Foundation
Related publications:
- Keusch, F., Leonard, M.M., Sajons, C., & Steiner, S. (2019). Using smartphone technology for research on refugees – Evidence from Germany. Sociological Methods & Research. Published online before print May 30, 2019. DOI: 10.1177/0049124119852377
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