Social Network Analysis in Migration Studies

Context: The importance of the involved stakeholders and their networks in vocational education and training (VET) focussing on international transfer and cooperation is highlighted in various empirical studies. A systematic empirical survey of these by means of social network analysis, however, has hardly been applied to date. This article is concerned with the development of social capital in the course of network formation and its sustainability. The object of investigation is the funded European VET innovation project AI Pioneers within the Erasmus+ program of the European Union. The main objective of the project is to establish and expand an international network in the context of VET in order to support the exchange of expertise on the use of artificial intelligence (AI) in education. Approach: To answer the research questions, the first step was to combine theoretical approaches from a social network perspective from psychology in relation to the analysis of interpersonal trust, sociology regarding the social capital approach and business administration by addressing the roles of actors in innovation processes. Among others, the social network perspective in this study is based on the work of Granovetter as well as Marsden and Campbell. For the data collection, a fully structured interview questionnaire and a semi-structured interview guideline were developed based on the theoretical framework of the study. In the second step, a multi-perspective egocentric network analysis was carried out: Data on a total of N = 10 egocentric networks were collected from the funded partners in the AI Pioneers project to gain an overall picture of the combined social capital and network structures. For the visualisation of the network data, the type of structured and standardised network maps was used. Findings: Regarding the establishment of social capital in the analysed innovation project AI Pioneers, it can be emphasised that a total of 74 relationships have been recorded in the 10 egocentric networks combined. In line with the project objectives, the education sector is addressed by the majority of the analysed relationships (n = 54), with (technical) vocational schools making up a substantial part of these. Focussing on the sustainability of the surveyed network structures: Most of the analysed relationships already existed before the project start and were consolidated during it (n = 57), while new ones were also established (n = 17). In addition, the continuous development of mutual trust and the need for equal cooperation is emphasised: A relatively high level of mutual trust can be recorded overall in the analysed egocentric networks (n = 55), while a low mutual trust is present in 19 relationships which is described due to e.g. asymmetrical power relations or a lack of commitment. The results show that the relationships analysed primarily contribute their resources in the form of expertise and their networking knowledge to the egocentric networks. Furthermore, a high level of interest and willingness to support the AI Pioneers project can be captured, particularly due to the novelty of the topic and the application of AI in VET. Conclusions: The study makes a significant contribution to VET research and its methodological set by using social network analysis with a combination of qualitative approaches for analysing egocentric networks from multiple perspectives. The importance of allocating resources to the creation of social capital regarding cooperation, network building and the sustainable maintenance of established structures can be emphasised. In this respect the benefits of a network-based approach can be highlighted in the context of the Erasmus+ program and the partnerships for innovation on forward-looking topics. In addition, the development of the two structured survey instruments in this study can be emphasised, which can be further developed on the basis of future research. Further quantitative network analyses would be valuable for VET research, especially against the background of innovation drivers and network formation, such as market and trend-related drivers due to demands and developments in the field of AI in education.

Purpose The purpose of this paper is to investigate when and how to best use social network analysis (SNA) in the supply chain management (SCM) discipline. In doing so, the study identifies SCM phenomena that have been examined from a social network perspective (SNA approach) in the SCM literature and highlights additional SCM phenomena that would be worth investigating using social network research. Then, the study critically investigates the application of SNA as a methodology (SNA method), with the goal of assessing and mitigating methodological risks in future studies. Design/methodology/approach This study carries out a systematic literature review of articles published in 11 top-tier SCM journals over a 20-year period. Findings First, while social network research has gained momentum especially since 2010, scholars are not yet entirely aware of the many possibilities the SNA approach offers to the SCM field. Second, expanded possibilities also hold for the development of SNA as a method. Originality/value The paper guides future SCM research by investigating when SNA is the right approach to use and how SNA as a method should be performed. Theoretically richer and practically more relevant research should result.

Conflict situations create changes. On the one hand, at the individual level, the subjects involved in the conflict are emotionally affected by it. On the other hand, at a social level, conflict management and its resolution transform in many cases, the context and the relationship of the people involved. How the conflict is managed will determine, to a large extent, the future of the relationship between the parties involved as well as the context. This chapter explores conflict management from a social network perspective in organizations. Scholars have used social network analysis (SNA) to understand the effects of a range of events in organizations. Conflict can spread through the fabric of the organization and disrupt business activity. Based on psychological and managerial literature, we first describe the concept of conflict management and SNA. Later, we analyze the interaction between those concepts. Finally, we explore how SNA becomes a powerful tool to diagnose and manage organizational conflict, as well as the change involved. Areas of future research are discussed.

Modeling, analysis, control, and management of complex social networks represent an important area of interdisciplinary research in an advanced digitalized world. In the last decade social networks have produced significant online applications which are running on top of a modern Internet infrastructure and have been identified as major driver of the fast growing Internet traffic. The "Second International Workshop on Modeling, Analysis and Management of Social Networks and Their Applications" (SOCNET 2018) held at Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany, on February 28, 2018, has covered related research issues of social networks in modern information society. The Proceedings of SOCNET 2018 highlight the topics of a tutorial on "Network Analysis in Python" complementing the workshop program, present an invited talk "From the Age of Emperors to the Age of Empathy", and summarize the contributions of eight reviewed papers. The covered topics ranged from theoretical oriented studies focusing on the structural inference of topic networks, the modeling of group dynamics, and the analysis of emergency response networks to the application areas of social networks such as social media used in organizations or social network applications and their impact on modern information society. The Proceedings of SOCNET 2018 may stimulate the readers' future research on monitoring, modeling, and analysis of social networks and encourage their development efforts regarding social network applications of the next generation.

An emerging trend in educational research is the use of social network theory and methodology to understand how teacher collaboration can support or constrain teaching, learning, and educational change. This article provides a critical synthesis of educational literature on school social networks among educators to advance our understanding of the embeddedness of teachers in the social context of schools. It focuses on how researchers currently use a social network perspective as a theoretical lens and methodology to frame studies on teacher collaboration in schools. Building on exemplary findings of recent studies, it shows that the pattern of social relationships among teachers may significantly enhance our understanding of the ways in which teacher collaboration takes place and contributes to student learning, teachers’ instructional practice, and the implementation of reform. Finally, limitations and future directions in the conceptualization, measurement, and analysis of school social networks are indicated.

The aim of the study is a practical analysis of social network services as a place to store multimedia resources that allow you to store and share digital photos, audio and video recordings, text files, presentations, and organize resource discussions for free. They can be used as educational materials (educational videos, photos on various topics, audio and video recordings of scientists' speeches, eyewitnesses of events, etc.), as well as means to store student video, photo, audio files and creative works. Method. Theoretical materials of the research are the best practices of foreign and domestic scientists in the field of network communications and their impact on the future specialists preparing in geography and tourism, namely articles, monographs, abstracts, dissertations. The study uses the method of theoretical materials analysis, as well as methods of observation, abstraction in identifying the qualification characteristics of social Internet networks. Content analysis (analysis of the social networks community messages content); statistical and comparative information analysis was carried out. Empirical research on the social Internet networks lies in creating and filling a community on the social Internet network, as well as engaging students in that community. Results. In the research it was found out that social networks can be used to solve the following tasks: to organize the collective work of students in the classroom (and outside it), which will be favourable to the communication, to gain the team experience; to ensure the development of the students personalized learning environment; to promote students independent learning, as everyone works in his own rhythm; to promote informal communication between the tutor and the students; to change the tutor's role, who will become an assistant, friend, mentor; to create digital educational content of the disciplines. The scientific novelty of the obtained results lies in the fact that on the comprehensive analysis of social internet networks, internet blogs, tourist internet resources basis, their place and role in the information and educational environment of higher education institutions are determined, in particular: the specifics of the content, prospects and mechanisms of the development of the social Internet networks from the point of view of training future tourists are determined; the dependence of the functions of the Social Internet Network, Internet blogs on their structural elements is established. Practical significance. The obtained scientific results are used in the educational process of future specialists in the field of training "Tourism", with the educational qualification "tourism expert, organizer of excursion and animation activities" when teaching the disciplines "study of local lore and tourism", "tourist work", "recreational geography", "geography of Ukraine", "professional competencies in tourism business", "organization of tourist activities". The research practices can be used to conduct tourist, museum, local history, excursion and other types of student's practice.

Interactions among fishery stakeholders can play an important role in mediating against the negative social and ecological consequences of fishery resource use. A number of studies have suggested that individual fishers draw on social relationships to access resources (e.g., fishing‐related information) embedded in social systems. Investment in social relationships can enable fishers to better locate and catch their target species, and group enforcement of norms can be used to protect the target resource from overexploitation. We employed observational and survey data collection techniques in assessing the relationship between the social network, social capital, and catch success of charter captains targeting salmonine fishes in a southeast Lake Michigan port. Using KliqueFinder software, we identified the structure of the social network within which charter captains communicated extensively and selectively about finding and catching their target species. We found that factors related to social capital helped inform captains' decisions about when to communicate, whom to communicate with, and whether to provide reliable information. Most captains, regardless of catch success, were cognizant that how they interacted with others affected their access to information and considered factors related to social capital when choosing to engage in informational exchanges. Captains whose catches exceeded the fleet's average catch were key communicators, holding relatively central positions within the social network. We integrate our findings with those of several other well‐documented cases to discuss the application of social network and capital theories to contemporary fisheries issues, as well as the potential advantages of viewing fisheries through a social network perspective.

In an attempt to appreciate the contribution that social network analysis might offer to the study of leisure, four distinctive, though not mutually exclusive, approaches to social network analysis are considered and an overall critique of the approach offered, paying special attention to the work of Wellman. Within this critique is a discussion of the ontological, epistemological and methodological problems confronting the social network perspective, particularly the works of those analysts, such as Stokowski (1994), who have attempted to merge structural analysis with more action-based perspectives. Some comparisons are made with figurational sociology and structuration theory, and attention is drawn to three central explanatory tools deployed within network analysis: the strength of weak ties, sociometry, and network density.

In this study, the structure of a service supply chain is analysed using social network analysis approach. Service supply chains consist of peoples and organisations connected in form of a network. The network is formed by the combination of ties between different players in the chain/network. These players are dependent upon each other and there exists flow of material or flow of information between players. Despite the longevity of the 'social networks' perspective, the product supply chains as well as the supply chain in services are less explored from the social network perspective. A case study on supply chain of property purchase has been discussed in this paper that is analysed with the help of social network analysis approach.

The emergence of the digital communication technologies such as the Internet have had a tremendous impact to the global economic, social and cultural landscape. The interconnectedness of computers and other digital devices had had significantly reduced the costs of communication and the transfer of information. Such technological development has spurred the rise of actors that facilitate the transfer of data between originators of information to its recipients. This, in turn accelerated the rise of multinational organizations as well as the proliferation of global business models. In fact, most of the social interactions involve intermediaries: online search engines, social network sites to the perplexed chains of distribution of commercial goods. The regulation of intermediary activities has been one of the most heated issues in the global agenda. The Global Financial Crisis that led to a collapse of large financial institutions showed the need for national governments to adjust their fiscal policies. Illegal distribution of the copyrighted content online has been another area in which states strive to find some sort of decent regulatory solution. The dissemination of information through intermediaries has been also brought to the public attention by court decisions in cases concerning Google Books, abuse of dominant position by Microsoft and, most recently, patent saga between Apple and Samsung. Although intermediaries play an important role in furthering the dissemination of information and alleviating information asymmetries, the involvement of intermediaries also could be seen as conferring additional transaction costs. At the same time, intermediaries also could be considered as facilitators of social interface. We start this paper by explaining how social network analysis could contribute to the legal scholarship and briefly discuss some key concepts used by the proponents of this methodology. Further, we argue that networks and (mutual) trust should be viewed as a form of social capital. Having introduced a number of cases previously explored by other social scientists, we submit that the establishment of trust-based relationships facilitates the transfer of values and resources. In the second part of this paper we suggest that further distinction between actual and deemed trust helps explain the creation as well as functioning of social networks and focus on the role of intermediaries in considering how they could contribute to the dissemination of information and economic resources. To do that, we provide to case-studies showing how the role of intermediaries can help build trust between remote actors and facilitate cooperation. These case-studies lead us to a more general observation that trust, as a form of social capital, could also be regarded as a public good.

Previous studies suggested that the implementation of note-taking strategies impacted students' learning process and performance. Research also suggested that collaborative learning facilitates students to learn from different views of interpreting information. The objective of this study was to investigate students' metacognitive skills and social networks while using electronic and paper-based enhanced guided notes. Students' worked in groups of three or four to complete the EGN. The impact of the collaborative note-taking activities on the students' collaboration processes was examined using social network analysis. Our findings revealed that students' cognitive and metacognitive strategies between electronic and paper-based EGN groups were relatively similar. Our data analysis of students' social networks revealed two clusters of students, high and low groups that represented the level of students' connectivity in a collaborations network. The findings suggested that the high group outperformed students in the low group in the use of cognitive, monitoring, and regulating strategies. Implications of the use of collaborative note-taking in engineering classroom will be discussed.

The social network model is powerful enough to provide for the analysis and study of a variety of application domains from daily life, including health care and health informatics. After the widespread appearance of automated tools capable of deriving and analyzing social networks, social network analysis (SNA) and mining in the health care domain has recently received considerable attention for its key role in understanding how various bodies within the health care system form communities and how they are socially connected with each other. This understanding helps enhance the organizational structures and process flows, among others. In this article, we show how SNA techniques can solve issues in the medical referral system in the Canadian health care system and the like, by analyzing the social network of general practitioners (GPs) and specialists (SPs). One of the main targets is to optimize the communication between GPs and SPs with hopes of decreasing the waiting time of patients to be seen by SPs. Various SNA and mining techniques are described and analyzed, backed by reporting some experimental results.

Recommender system is the system which, by using automated information filtering technology, recommends products or services to the customers who are likely to be interested in. Those systems are widely used in many different Web retailers such as Amazon.com, Netfix.com, and CDNow.com. Various recommender systems have been developed. Among them, Collaborative Filtering (CF) has been known as the most successful and commonly used approach. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. However, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting in advance whether the performance of CF recommender system is acceptable or not is practically important and needed. In this study, we propose a decision making guideline which helps decide whether CF is adoptable for a given application with certain transaction data characteristics. Several previous studies reported that sparsity, gray sheep, cold-start, coverage, and serendipity could affect the performance of CF, but the theoretical and empirical justification of such factors is lacking. Recently there are many studies paying attention to Social Network Analysis (SNA) as a method to analyze social relationships among people. SNA is a method to measure and visualize the linkage structure and status focusing on interaction among objects within communication group. CF analyzes the similarity among previous ratings or purchases of each customer, finds the relationships among the customers who have similarities, and then uses the relationships for recommendations. Thus CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. Under the assumption that SNA could facilitate an exploration of the topological properties of the network structure that are implicit in transaction data for CF recommendations, we focus on density, clustering coefficient, and centralization which are ones of the most commonly used measures to capture topological properties of the social network structure. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. We explore how these SNA measures affect the performance of CF performance and how they interact to each other. Our experiments used sales transaction data from H department store, one of the well?known department stores in Korea. Total 396 data set were sampled to construct various types of social networks. The dependant variable measuring process consists of three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used UCINET 6.0 for SNA. The experiments conducted the 3-way ANOVA which employs three SNA measures as dependant variables, and the recommendation accuracy measured by F1-measure as an independent variable. The experiments report that 1) each of three SNA measures affects the recommendation accuracy, 2) the density's effect to the performance overrides those of clustering coefficient and centralization (i.e., CF adoption is not a good decision if the density is low), and 3) however though the density is low, the performance of CF is comparatively good when the clustering coefficient is low. We expect that these experiment results help firms decide whether CF recommender system is adoptable for their business domain with certain transaction data characteristics.

PurposeThe purpose of this paper is to examine the effects of individual difference variables and social relationships on student learning outcomes of short-term study abroad programs.Design/methodology/approachThis study used a social network analysis (SNA) approach to examine the effects of friendship, advice and communication networks on student learning outcomes.FindingsResults indicated that demographic characteristics (e.g. sex, years of work experience) did not influence learning outcomes nor the enjoyment of the experience. Social networks positively influenced students’ perceived improvement in managerial skills, their ability to reflect on their international experience and their intercultural sensitivity.Research limitations/implicationsSocial relationships may be an important factor to consider in understanding the relationship between short-term study abroad programs and learning outcomes.Practical implicationsProgram directors and faculty members need to consider the design of assignments and activities that may facilitate the development of specific types of social relationships (e.g. friendship, communication and advice). These specific social relationships may have unique influences on specific learning outcomes of short-term study abroad programs.Originality/valueThis study is the first study that examined the effects of different types of social relationships on learning outcomes for short-term study abroad programs. The results have important implications for both future research and the design of international study-abroad programs.

Agricultural innovation has tremendous potentials to improve the welfare of the rural poor. Yet, many new technologies that seem profitable in demonstration plots are not widely adopted due to inadequate social groups linking the farmers to the researchers which result to non-effective information dissemination. There is no adequate link between the farmers and the social groups which are very pivotal to the adoption of innovation and its eventual usage. This study therefore looked at social network and innovation dissemination among farmers in Kwara state Nigeria. This research specifically examined the impact of social network among the farmers in the study area and estimated the correlation of individual farmer’s choices and social network behaviour. A two-stage approach was used in data selection; the first stage was purposive and second involved the random selection technique to collect data from 125 respondents in the study area. Descriptive statistic, Social Network Analysis (SNA), and Qap correlation were the tools employed. The result of the analysis showed that farmers who are members of social group adopt innovation faster. The p-value at 5% signified that there is no correlation between the farmer choice behaviour and social network behaviour. This implies that farmer tend to behave differently under different conditions as regards their choice of innovation adoption., However, when farmers are members of a social group, their decision tend to be different from when they were not and thus, there is a need for adequate information link between researchers and the farmers. Female farmers should be encouraged to join social group as measure to enhance innovation adoption. Keywords: Social Network Analysis (SNA), Qap Correlation and Innovation