![]() In this chapter, we address one of the most significant challenges of using this strategy by exploring the biases it may present and the possible ways to resolve them. While the advantages of sampling migrants using SNS and surveying them online are clear, the drawbacks of this method-and, even more so, the potential solutions-constitute an almost unexplored field. The spread of social media usage among migrants has led researchers to look at the potential that Social Networking Sites (SNS) have for migration studies with respect to extracting and analyzing big data, conducting ethnography online, and reaching migrant respondents through SNS advertising. The observed constraints relate to the definition of a target group, the management of incentives online, and the anonymity issues of online surveys.Ĭhoosing a methodology for migrant surveys usually is a complicated issue for a number of reasons, including the lack of information about sampling frames, and migrants’ status as a hard-to-reach population. ![]() We outline observations from the fieldwork (selection of seeds, formation of referral chains, etc.), and discuss the challenges of using Web-based RDS by focusing on the barriers to referral chain formation related to RDS assumptions and study design. We examine this issue by using the example of a survey of Polish multiple migrants worldwide conducted in 2018–2019. ![]() While the RDS method can be powerful in fact-to-face interviews, its usefulness in Internet surveys is debatable. The goal of this chapter is to outline the opportunities and challenges associated with using Web-based RDS for researching migrant populations. However, its implementation is not an easy task and does not succeed in all migratory settings. The Web-based Respondent Driven Sampling (RDS) method addresses many of the challenges occurring in such a context. The richness of the growing variety of geographical and temporal migrant trajectories pose particular challenges for quantitative researchers studying such spatially dispersed populations for which sampling frames are not available. Internet surveys are the future of migration studies given that migrants engage more and more often in multidirectional movements and reside in multiple destination countries. The main goal of this chapter is to raise awareness of the additional technology layer that impacts translation and adaptation, with an ultimate goal to improve translation and adaptation processes, and the outcomes of migration research. Real-life examples come from our own experiences in international and migration research, as well as from a review of existing reports and research articles. Frameworks from the software localization field are consulted and transferred to the context of computerized multilingual surveys with respect to their impact on source questionnaire design and on translation and adaptation. In line with the technology-based focus of this book, the second part focuses on computerized surveys and on the interplay between technology, language, and culture. The first part outlines good practices in questionnaire translation. This chapter examines the technical challenges involved in translating and adapting measurement instruments, i.e., questionnaires, for migration research. Nevertheless, we also found that a small but substantial subgroup of interviewees with little or no reading skills used the audio files often. However, illiterate interviewees are more likely to take advantage of the interviewer’s support to read the questions aloud than to use the audio files. Although native-speaking interviewers can increase cooperation and help to not exclude illiterate individuals, they also can encourage a higher social desirability bias. Subsequently, using the data from the first wave of the German refugee study ReGES, in which both strategies were offered as a combined approach, we consider their effectiveness and practicability in more detail. ![]() We discuss the pros and cons of both strategies. Two strategies can be used to avoid systematically excluding this population: offering interviews with native-speaking interviewers or using computer-assisted self-interviewing (CASI) with additional audio files that enable respondents to listen to a questionnaire. In addition to the need to provide interviews for immigrants in their native language, it must be taken into account that a considerable proportion of this group has poor or no reading skills in their native language. This chapter focuses on specific challenges to surveying newly arrived immigrants with a focus on refugees.
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