Social networks in migration and migrant incorporation: New developments and challenges

Migration cannot be understood without comprehending the social networks that surround and sustain it. Research over the past several decades has increasingly shown that social networks are crucial to explain what causes migration, how migration takes place, and what its consequences are for migrants, their families, and their sending and receiving communities. Reflecting this growing awareness, scholarship at the network-migration nexus has steadily grown in the past 10–20 years, as measured by the absolute and relative frequencies of relevant articles (Figure 1).¹ The field is now reaching a stage of maturation in which social networks are not evoked simply as suggestive imagery or impressionistic analogies, but rather they are regularly studied with theories, data collection techniques, and analytic methods from social network analysis and network science.

Against the backdrop of this expanding scientific effort, the current Special Issue aims to highlight and assess new developments and challenges in the study of social networks and migration. We introduce the issue by first reviewing central themes and bibliographic references in the study of networks and migration in the first quarter of the new century, as revealed by patterns of keyword co-occurrence and reference co-citation in the relevant literature. Second, after briefly summarizing the 12 contributions to this issue, we discuss four major developments and two dimensions of variation they demonstrate. We conclude by outlining the future directions and challenges that emerge from this issue in the study of migration as a networked phenomenon.

With multiple recent reviews synthesizing available evidence and major theories in the field, migration researchers are now well aware of the essential role played by social networks in shaping antecedents, processes, and outcomes of migration (Bilecen et al., 2018; Bilecen & Lubbers, 2021; Garip & Asad, 2015; Gold, 2005; Lubbers et al., 2018; Lubbers & Molina, 2021). Networks around migration have been studied both with a social network analytic approach and with a relational or cultural approach (Bilecen & Lubbers, 2021), at times combined in the same study. The former perspective focuses on network structures, properties, and positions, favouring quantitative measurement and methods. The latter framework addresses meanings, perceptions, and practices within and behind social ties while relying predominantly on qualitative research designs. The many strands of knowledge accumulated by these two approaches are reflected in the landscape of relevant literature since 2000, as captured by co-occurrence of article keywords and the co-citation of common bibliographic references.

Many of the themes and references mentioned in the previous section return prominently in the 12 articles of this special issue. Among these, the first subset of contributions proposes a relational approach to the study of migrants' personal networks, mostly relying on qualitative or mixed-methods research designs. Aydemir (2025) examines the personal networks of migrant academics in Britain, looking at overlaps and shifting boundaries between different types of relationships and their subjective meanings. Bulled (2025) studies the way that early settlement and integration trajectories of recent asylum seekers in Greece are influenced by their personal networks. Cases (2025) compares the support networks of Filipino nurses, domestic workers, and care workers in New York and London, paying special attention to the way they respond and adapt to individual life events and macro-level policies. Tomás and Molina's (2025) article is concerned with mobile retirees between Spain and Switzerland, comparing first-time migrants, return migrants, onward migrants, and bi-local individuals, and examining the association between their personal networks and mobility trajectories. Finally, D'Angelo and Ryan (2025) offer a broader discussion of methodological issues in qualitative network analysis, using examples from their recent work to illustrate notions of conceptual reflexivity in the study of migrant networks.

A second subset of articles in this issue proposes more deductive and quantitative (or mixed-methods) designs aiming to compare different migrant groups or test hypotheses about antecedents and consequences of social networks for migrants. Bilecen et al. (2025) analyse personal networks as determinants of loneliness among Chinese students in Germany. Fraudatario et al. (2025) use network concepts and data to operationalize the notion of mixed embeddedness among Sri Lankan entrepreneurs in Naples, Italy, and Pakistani entrepreneurs in Manchester, UK. Hoór and Bellotti (2025) investigate how different features and aspects of personal networks, including social support and negative ties, influence Hungarian migrants' return experiences in their country of origin. Jeroense et al. (2025) propose a systematic comparison of extended acquaintanceship networks between migrants and non-migrants in the Netherlands, as well as between different ethnic groups and generations among migrants, using rich survey data to estimate ego-network size and ethnic homogeneity. Solano (2025) tests different hypotheses about the network determinants of negative social capital among rural–urban migrant entrepreneurs in Uganda. Mouw et al. (2025) examine unique longitudinal data to compare the personal networks of Chinese migrants in the USA before and after the COVID-19 crisis. Finally, McMillan (2025) turns attention to macro-level networks of inter-country migration flows: she uses valued Exponential Random Graph Models to test hypotheses derived from long-standing theories of migration and hypotheses about the role of endogenous network patterns in these flows.

In addition to the four themes discussed above, this issue also points to important dimensions of variation – both theoretical and methodological – in research about social networks and migration. We highlight two of them: the role of networks as causes or consequences in theory building, and variation in the methods used to connect theory to empirical data.

As far as the first dimension is concerned, migration scholars have conceptualized social networks as either causes (“independent variables”) or consequences (“dependent variables”) of other phenomena. In social network research, these two approaches have been called ‘network theories’ and ‘theories of networks’, respectively (Borgatti & Lopez-Kidwell, 2011). With network theories of migration, social network constructs are the main causes of interest, and researchers study the effects, impacts, or consequences of social networks for micro- or macro-level outcomes in migration and migrant integration. In this issue, for example, Bilecen et al. (2025) view personal network characteristics as a potential explanation for patterns of loneliness among migrant students; Hoór and Bellotti (2025) study migrants' personal networks as a cause of different experiences and evaluations of return to the origin communities. With theories of networks in migration, conversely, researchers consider the antecedents and causes of social networks and their characteristics in migrant populations. Jeroense et al. (2025), for instance, posit that migrants' extended acquaintanceship networks are influenced by generation, out-group bias, ethnic composition of residential neighbourhoods, and degree of participation in interaction foci. Mouw and colleagues' (2025) contribution theorizes that the COVID-19 crisis had significant impacts on interaction frequency and new friendship formation among Chinese migrants in the USA.

Theories of networks in migration are often proposed, more or less explicitly, in comparative studies of different migration contexts (see Section “Comparing networks between groups”). Here, social networks are treated as the “dependent variable” that changes in response to contextual characteristics. In certain comparative studies, social networks are also regarded as a mediating variable between context and the dependent phenomenon of interest: contexts shape networks, which in turn, influence migration outcomes in domains such as occupational attainment, cultural integration, and health. Finally, the same study may consider social networks as both causes and consequences of migration-related phenomena. Tomás and Molina (2025), for example, investigate how pre-retirement migration trajectories shape the personal networks of migrant retirees (networks as consequences), and how personal ties, in turn, influence their mobility decisions (networks as causes).

Regarding the second, methodological dimension, social network studies of migration mirror the field of social network research more broadly in the breadth and diversity of methods employed for data collection and analysis. Some of this variety is displayed in the current issue, together with important innovations in both quantitative and qualitative methods. The more cutting-edge quantitative techniques in this issue range from the use of valued Exponential Random Graph Models to analyse new migration flow estimates between countries (McMillan, 2025), to the analysis of aggregate relational data for estimating acquaintanceship network size and diversity via network scale-up methods (Jeroense et al., 2025), to the modelling of longitudinal ego-network data collected with innovative probability-based link-tracing sampling procedures (Mouw et al., 2025). Other articles in this issue contribute to methodological advances in mixed and qualitative designs, heeding recent calls for better exploration of mixed methods in research on networks and migration (Bilecen & Lubbers, 2021). Hoór and Bellotti (2025) and Tomás and Molina (2025), for example, propose novel methods for reconstructing personal networks from a combination of in-depth interviews and computer-assisted personal network interviews. D'Angelo and Ryan (2025) suggest new directions in qualitative methods for relational research on migration, showing how to adopt the lens of reflexivity not just in the collection of data but also in the selection of concepts we use to analyse those data and communicate results.

Finally, Tomás and Molina's (2025) work also exemplifies another kind of advancement in research designs and methods – the use of network concepts and techniques to overcome the pitfalls of ‘migranticization’ and ‘methodological nationalism’ in migration studies (Dahinden, 2016). Rather than relying on traditional categories of ethnicity or migration background, which may be limited in capturing the heterogeneity and complexity of migration phenomena in the real world, Tomás and Molina (2025) take mobility between two countries (Spain and Switzerland) as the starting point in defining their population of interest and designing sampling procedures. In this way, they also show how social network analysis can be effectively used to give operational precision to theoretical concepts such as dual frame of reference and bifocality (Lubbers & Molina, 2021), and to account for the multidirectional nature of contemporary migration processes as observed in onward, return, circular, and bi-local migrant populations (Bilecen & Lubbers, 2021).

The four threads and two dimensions of variation in this Special Issue point to important avenues and potential challenges in future research on migration and social networks. First, the emerging emphasis on the contexts of migrant networks aligns well both with long-standing research on the way spatial environments shape social networks (Small & Adler, 2019), and with more recent interest in ‘network ecology’ – the study of how institutional, cultural, and physical settings influence network configurations and dynamics (Doehne et al., 2024). This convergence may lead to promising new lines of theorization and empirical work in the near future.

A second important direction is the pursuit of more systematic and comprehensive comparisons between populations and contexts. These may be comparisons between migrant and non-migrant groups, with the goal of discerning what exactly is distinctive about the migration experience and migrant condition in network structures and processes. There may also be comparisons between migrant subgroups, aiming to illuminate the internal heterogeneity of migrant populations and the way migrant networks and life outcomes are affected by the intersection between migration status and other factors – such as gender, race/ethnicity, social class, the life course, or geography.

A third set of future directions and challenges in the field is concerned with the study of network change and dynamics. The need for more and better longitudinal studies of networks in migrant populations – particularly those that span the period before, during, and after migration – has already been stressed elsewhere (Bilecen & Lubbers, 2021; Lubbers & Molina, 2021). In addition, recent efforts to integrate life course and network research (Vacchiano et al., 2024) and new evidence about migrants' vulnerability to life events with adverse impacts on health and well-being (Loi et al., 2024) suggest to better incorporate life course data and analyses in the study of social networks and migration.

Research on network dynamics in migration would also benefit from simulations and Agent-Based Models (ABMs; Bianchi & Squazzoni, 2015; McAlpine et al., 2021). ABMs are especially useful to study evolving, connected systems in which adaptive agents are both influenced by networks (e.g. their local network determines the opportunities available to them or their likelihood to adopt a behaviour) and able to change them (e.g., to dissolve certain ties and activate new ones). ABMs, as well as mixed-methods approaches, would also enable scholars to more rigorously identify the specific causal mechanisms underlying the effects of networks on migration outcomes (Garip & Asad, 2015), and to explore how micro-level conditions and behaviours aggregate to produce macro-level patterns in networked populations (Stadtfeld & Amati, 2021). Agent-based modelling is a major focus in computational social science, the study of social phenomena and human behaviour with computational methods, often applied to large digital data sets. As stressed in recent discussions of computational social science in migration studies (Drouhot et al., 2023), computational methods and digital data hold great promise for advancing knowledge on network mechanisms and dynamics in migration and migrant integration.

Finally, the more extensive and rigorous study of negative ties is another future challenge for research on networks and migration. Different articles in this Special Issue point to the need to better attend to the negative aspects of social relationships and personal networks in migrant populations. This effort should include more precise conceptualizations and operationalizations of notions such as difficult relationships, ambivalent ties, and negative social capital. Greater dialogue between migration studies and research on negative ties in general populations (Offer, 2021) has the potential to strongly advance research on negative ties in migrant networks and their impacts on a wide variety of migration outcomes, including health and well-being, family life, and labour market incorporation. Taken together, these four avenues for future research foreshadow numerous opportunities to leverage recent theoretical and methodological advances to improve our understanding of social networks, their antecedents, and their consequences in migration and migrant incorporation.