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

IF 1.6 3区 社会学 Q2 DEMOGRAPHY
Raffaele Vacca, Başak Bilecen, Miranda J. Lubbers
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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).<sup>1</sup> 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.</p><p>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.</p><p>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., <span>2018</span>; Bilecen &amp; Lubbers, <span>2021</span>; Garip &amp; Asad, <span>2015</span>; Gold, <span>2005</span>; Lubbers et al., <span>2018</span>; Lubbers &amp; Molina, <span>2021</span>). Networks around migration have been studied both with a social network analytic approach and with a relational or cultural approach (Bilecen &amp; Lubbers, <span>2021</span>), 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.</p><p>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 (<span>2025</span>) 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 (<span>2025</span>) studies the way that early settlement and integration trajectories of recent asylum seekers in Greece are influenced by their personal networks. Cases (<span>2025</span>) 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 (<span>2025</span>) 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 (<span>2025</span>) 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.</p><p>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. (<span>2025</span>) analyse personal networks as determinants of loneliness among Chinese students in Germany. Fraudatario et al. (<span>2025</span>) 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 (<span>2025</span>) 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. (<span>2025</span>) 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 (<span>2025</span>) tests different hypotheses about the network determinants of negative social capital among rural–urban migrant entrepreneurs in Uganda. Mouw et al. (<span>2025</span>) examine unique longitudinal data to compare the personal networks of Chinese migrants in the USA before and after the COVID-19 crisis. Finally, McMillan (<span>2025</span>) 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.</p><p>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.</p><p>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 &amp; Lopez-Kidwell, <span>2011</span>). With <i>network theories of migration</i>, 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. (<span>2025</span>) view personal network characteristics as a potential explanation for patterns of loneliness among migrant students; Hoór and Bellotti (<span>2025</span>) study migrants' personal networks as a cause of different experiences and evaluations of return to the origin communities. With <i>theories of networks in migration</i>, conversely, researchers consider the antecedents and causes of social networks and their characteristics in migrant populations. Jeroense et al. (<span>2025</span>), 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' (<span>2025</span>) contribution theorizes that the COVID-19 crisis had significant impacts on interaction frequency and new friendship formation among Chinese migrants in the USA.</p><p>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 (<span>2025</span>), 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).</p><p>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, <span>2025</span>), to the analysis of aggregate relational data for estimating acquaintanceship network size and diversity via network scale-up methods (Jeroense et al., <span>2025</span>), to the modelling of longitudinal ego-network data collected with innovative probability-based link-tracing sampling procedures (Mouw et al., <span>2025</span>). 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 &amp; Lubbers, <span>2021</span>). Hoór and Bellotti (<span>2025</span>) and Tomás and Molina (<span>2025</span>), 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 (<span>2025</span>) 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.</p><p>Finally, Tomás and Molina's (<span>2025</span>) 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, <span>2016</span>). 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 (<span>2025</span>) 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 &amp; Molina, <span>2021</span>), and to account for the multidirectional nature of contemporary migration processes as observed in onward, return, circular, and bi-local migrant populations (Bilecen &amp; Lubbers, <span>2021</span>).</p><p>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 <i>contexts of migrant networks</i> aligns well both with long-standing research on the way spatial environments shape social networks (Small &amp; Adler, <span>2019</span>), 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., <span>2024</span>). This convergence may lead to promising new lines of theorization and empirical work in the near future.</p><p>A second important direction is the pursuit of more <i>systematic and comprehensive comparisons</i> 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.</p><p>A third set of future directions and challenges in the field is concerned with the study of <i>network change and dynamics</i>. 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 &amp; Lubbers, <span>2021</span>; Lubbers &amp; Molina, <span>2021</span>). In addition, recent efforts to integrate life course and network research (Vacchiano et al., <span>2024</span>) and new evidence about migrants' vulnerability to life events with adverse impacts on health and well-being (Loi et al., <span>2024</span>) suggest to better incorporate life course data and analyses in the study of social networks and migration.</p><p>Research on network dynamics in migration would also benefit from simulations and Agent-Based Models (ABMs; Bianchi &amp; Squazzoni, <span>2015</span>; McAlpine et al., <span>2021</span>). 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 &amp; Asad, <span>2015</span>), and to explore how micro-level conditions and behaviours aggregate to produce macro-level patterns in networked populations (Stadtfeld &amp; Amati, <span>2021</span>). 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., <span>2023</span>), computational methods and digital data hold great promise for advancing knowledge on network mechanisms and dynamics in migration and migrant integration.</p><p>Finally, the more extensive and rigorous study of <i>negative ties</i> 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, <span>2021</span>) 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.</p>","PeriodicalId":48011,"journal":{"name":"International Migration","volume":"63 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/imig.13373","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Migration","FirstCategoryId":"90","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/imig.13373","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
引用次数: 0

Abstract

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.

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移民和移民融合中的社会网络:新的发展和挑战
如果不了解围绕和维持移民的社会网络,就无法理解移民。过去几十年的研究越来越多地表明,社交网络在解释移民的原因、移民是如何发生的,以及移民对移民、他们的家庭以及他们的发送和接收社区的影响方面至关重要。从相关文章的绝对频率和相对频率来看,在过去的10-20年里,关于网络迁移关系的学术研究稳步增长,反映了这种日益增长的意识(图1)该领域现在正达到一个成熟阶段,在这个阶段中,社会网络不是简单地作为暗示性的图像或印象主义的类比来唤起,而是经常用社会网络分析和网络科学的理论、数据收集技术和分析方法来研究它们。在这种不断扩大的科学努力的背景下,本期特刊旨在强调和评估社会网络和移民研究中的新发展和挑战。本文首先回顾了新世纪前25年网络与移民研究的中心主题和参考文献,并通过相关文献的关键词共现和参考文献共被引模式来揭示这一问题。其次,在简要总结了对这个问题的12个贡献之后,我们讨论了四个主要的发展和它们所展示的两个变化维度。最后,我们概述了未来的方向和挑战,从这个问题中出现的迁移作为一个网络现象的研究。最近的多项综述综合了该领域的现有证据和主要理论,移民研究人员现在已经充分意识到社交网络在塑造移民的前提、过程和结果方面发挥的重要作用(Bilecen等人,2018;Bilecen,•吕贝尔2021;Garip,阿萨德,2015;金,2005;Lubbers等人,2018;•吕贝尔,莫利纳,2021)。围绕移民的网络已经用社会网络分析方法和关系或文化方法(Bilecen &amp;Lubbers, 2021),有时在同一研究中结合起来。前一种观点关注网络的结构、性质和位置,倾向于定量测量和方法。后一种框架主要依靠定性研究设计,解决社会关系内部和背后的意义、观念和实践。通过这两种方法积累的许多知识链反映在2000年以来的相关文献景观中,如文章关键词的共现和共同书目参考文献的共引所捕获的那样。上一节提到的许多主题和参考文献在本期特刊的12篇文章中再次出现。其中,第一个贡献子集提出了一种关系方法来研究移民的个人网络,主要依靠定性或混合方法的研究设计。Aydemir(2025)研究了英国移民学者的个人网络,研究了不同类型关系及其主观含义之间的重叠和变化边界。bulbull(2025)研究了近期在希腊寻求庇护者的早期定居和融入轨迹受到其个人网络影响的方式。案例(2025)比较了纽约和伦敦的菲律宾护士、家政工人和护理人员的支持网络,特别关注他们对个人生活事件和宏观政策的反应和适应方式。Tomás和Molina(2025)的文章关注的是西班牙和瑞士之间的流动退休人员,比较了首次移民、返回移民、继续移民和双本地个人,并研究了他们的个人网络与流动轨迹之间的关系。最后,D’angelo和Ryan(2025)对定性网络分析中的方法论问题进行了更广泛的讨论,他们使用他们最近工作中的例子来说明移民网络研究中的概念反射概念。本期文章的第二个子集提出了更多的演绎和定量(或混合方法)设计,旨在比较不同的移民群体或检验关于移民社会网络的前因和后果的假设。Bilecen等人(2025)分析了个人网络作为德国中国留学生孤独感的决定因素。Fraudatario等人(2025)利用网络概念和数据在意大利那不勒斯的斯里兰卡企业家和英国曼彻斯特的巴基斯坦企业家中实现了混合嵌入性的概念。Hoór和Bellotti(2025)研究了个人网络的不同特征和方面,包括社会支持和负面关系,如何影响匈牙利移民在原籍国的返回经历。Jeroense等人。 (2025)利用丰富的调查数据来估计自我网络规模和种族同质性,对荷兰移民和非移民之间以及移民中不同种族和世代之间的扩展熟人网络进行系统比较。索拉诺(2025)检验了关于乌干达城乡移民企业家负社会资本的网络决定因素的不同假设。Mouw等人(2025)研究了独特的纵向数据,以比较COVID-19危机前后在美国的中国移民的个人网络。最后,McMillan(2025)将注意力转向国家间移民流动的宏观层面网络:她使用有价值的指数随机图模型(Exponential Random Graph Models)来检验从长期存在的移民理论中得出的假设,以及关于内生网络模式在这些流动中的作用的假设。除了上面讨论的四个主题之外,这个问题还指出了在关于社会网络和移民的研究中,理论和方法上的变化的重要维度。我们强调其中的两个:网络作为理论构建的原因或结果的作用,以及用于将理论与经验数据联系起来的方法的变化。就第一个维度而言,移民学者将社会网络概念化为其他现象的原因(“自变量”)或结果(“因变量”)。在社会网络研究中,这两种方法分别被称为“网络理论”和“网络理论”(Borgatti &amp;Lopez-Kidwell, 2011)。在迁移的网络理论中,社会网络的构建是研究的主要原因,研究者研究社会网络对迁移和移民融合的微观或宏观结果的影响、影响或后果。例如,在本期中,Bilecen等人(2025)将个人网络特征视为流动学生孤独感模式的潜在解释;Hoór和Bellotti(2025)研究了移民的个人网络作为返回原籍社区的不同经验和评估的原因。相反,在迁移网络理论中,研究人员考虑了迁移人口中社会网络的前提和原因及其特征。例如,Jeroense等人(2025)假设移民扩大的熟人网络受到世代、群体外偏见、居住社区的种族构成和参与互动焦点程度的影响。Mouw及其同事(2025)的贡献理论认为,COVID-19危机对美国中国移民之间的互动频率和新的友谊形成产生了重大影响。在对不同迁移背景的比较研究中,经常提出或多或少明确的迁移网络理论(见“群体之间的网络比较”一节)。在这里,社会网络被视为“因变量”,随着上下文特征的变化而变化。在某些比较研究中,社会网络也被视为背景和兴趣依赖现象之间的中介变量:背景塑造网络,反过来影响职业成就、文化融合和健康等领域的移民结果。最后,同样的研究可能认为社会网络是移民相关现象的原因和结果。例如,Tomás和Molina(2025)研究了退休前的移民轨迹如何塑造退休移民的个人网络(网络作为后果),以及个人关系如何反过来影响他们的流动决策(网络作为原因)。关于第二个方法学维度,移民的社会网络研究在数据收集和分析方法的广度和多样性方面更广泛地反映了社会网络研究领域。本期杂志展示了其中的一些变化,以及定量和定性方法的重要创新。本期更尖端的定量技术包括使用有价值的指数随机图模型来分析国家之间的新移民流量估算(McMillan, 2025),以及通过网络放大方法分析聚合关系数据以估计熟人网络规模和多样性(Jeroense等人,2025)。到利用创新的基于概率的链接追踪抽样程序收集的纵向自我网络数据的建模(Mouw等人,2025)。本期的其他文章对混合和定性设计的方法进步做出了贡献,关注了最近在网络和迁移研究中更好地探索混合方法的呼吁(Bilecen &amp;•吕贝尔,2021)。 例如,Hoór和Bellotti(2025)以及Tomás和Molina(2025)提出了通过深度访谈和计算机辅助的个人网络访谈相结合来重建个人网络的新方法。D’angelo和Ryan(2025)提出了迁移关系研究定性方法的新方向,展示了如何不仅在收集数据时采用反思性的视角,而且在选择我们用来分析这些数据和交流结果的概念时也采用反思性的视角。最后,Tomás和Molina(2025)的工作也体现了研究设计和方法的另一种进步-使用网络概念和技术来克服移民研究中的“移民化”和“方法论民族主义”的陷阱(Dahinden, 2016)。Tomás和Molina(2025)没有依赖传统的种族或移民背景类别,这可能在捕捉现实世界中移民现象的异质性和复杂性方面受到限制,而是将两个国家(西班牙和瑞士)之间的流动性作为定义其感兴趣的人口和设计抽样程序的起点。通过这种方式,他们还展示了如何有效地使用社会网络分析来为理论概念提供操作精度,如双重参考框架和双局部性(Lubbers &amp;Molina, 2021),并考虑到当代移民过程的多向性,如在前进、返回、循环和双地移民人口中观察到的(Bilecen &amp;•吕贝尔,2021)。本期特刊中的四个线索和两个维度的变化指出了未来移民和社会网络研究的重要途径和潜在挑战。首先,对移民网络背景的新兴强调与长期以来对空间环境塑造社会网络方式的研究(Small &amp;Adler, 2019),以及最近对“网络生态学”的兴趣——研究制度、文化和物理环境如何影响网络配置和动态(Doehne et al., 2024)。这种趋同可能在不久的将来导致有希望的理论化和实证工作的新路线。第二个重要的方向是在人口和环境之间进行更系统和全面的比较。这些可能是移民和非移民群体之间的比较,目的是辨别网络结构和过程中移民经验和移民状况的独特之处。还可以对移民亚群体进行比较,旨在阐明移民人口的内部异质性,以及移民身份与其他因素(如性别、种族/民族、社会阶层、生命历程或地理位置)之间的交集对移民网络和生活结果的影响方式。该领域的第三个未来方向和挑战与网络变化和动态的研究有关。对移民人口网络进行更多、更好的纵向研究的必要性——特别是那些跨越移民之前、期间和之后的研究——已经在其他地方得到了强调(Bilecen &amp;•吕贝尔2021;•吕贝尔,莫利纳,2021)。此外,最近整合生命历程和网络研究的努力(Vacchiano et al., 2024)以及关于移民易受对健康和福祉有不利影响的生活事件影响的新证据(Loi et al., 2024)建议在社会网络和移民的研究中更好地纳入生命历程数据和分析。迁移中的网络动力学研究也将受益于仿真和基于agent的模型(ABMs);比安奇,Squazzoni, 2015;McAlpine et al., 2021)。在这些系统中,自适应主体既受到网络的影响(例如,它们的本地网络决定了它们可用的机会或它们采取某种行为的可能性),又能够改变它们(例如,解除某些联系并激活新的联系)。ABMs以及混合方法方法也将使学者们能够更严格地确定网络对迁移结果影响的具体因果机制(Garip &amp;Asad, 2015),并探索微观层面的条件和行为如何聚集在一起,在网络化人群中产生宏观层面的模式(Stadtfeld &amp;阿玛蒂,2021)。基于主体的建模是计算社会科学的一个主要焦点,用计算方法研究社会现象和人类行为,通常应用于大型数字数据集。正如最近关于移民研究中计算社会科学的讨论所强调的那样(Drouhot et al., 2023),计算方法和数字数据对于推进移民和移民融合中的网络机制和动态知识具有很大的希望。 最后,对负面关系的更广泛和严格的研究是未来网络和移民研究的另一个挑战。本期特刊的不同文章指出,需要更好地关注移徙人口的社会关系和个人网络的消极方面。这种努力应该包括更精确的概念化和概念的操作化,如困难的关系、矛盾的关系和消极的社会资本。移民研究与一般人群负面联系研究之间的更大对话(Offer, 2021年)有可能有力地推进关于移民网络中的负面联系及其对各种移民结果(包括健康和福祉、家庭生活和劳动力市场融入)影响的研究。总的来说,这四个未来研究的途径预示着许多机会,可以利用最近的理论和方法进步来提高我们对社会网络的理解,它们的前因后果,以及它们在移民和移民融合中的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.70
自引率
10.50%
发文量
130
期刊介绍: International Migration is a refereed, policy oriented journal on migration issues as analysed by demographers, economists, sociologists, political scientists and other social scientists from all parts of the world. It covers the entire field of policy relevance in international migration, giving attention not only to a breadth of topics reflective of policy concerns, but also attention to coverage of all regions of the world and to comparative policy.
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