A model for the multiplex dynamics of two-mode and one-mode networks,with an application to employment preference,friendship, and advice

We propose a new stochastic actor-oriented model for the co-evolution of two-mode and one-mode networks. The model posits that activities of a set of actors, represented in the two-mode network, co-evolve with exchanges and interactions between the actors, as represented in the one-mode network. The model assumes that the actors, not the activities, have agency.     

Multiple partitioning of multiplex signed networks: Application to European parliament votes

For more than a decade, graphs have been used to model the voting behavior taking place in parliaments. However, the methods described in the literature suffer from several limitations. The two main ones are that 1) they rely on some temporal integration of the raw data, which causes some information loss; and/or 2) they identify groups of antagonistic voters, but not the context associated with their occurrence. In this article, we propose a novel method taking advantage of multiplex signed graphs to solve both these issues. It consists in first partitioning separately each layer, before grouping these partitions by similarity. We show the interest of our approach by applying it to a European Parliament dataset.     

Revisiting clientelism: A network analysis of problem-solving networks in Argentina

Clientelism is a problem-solving network where brokers solve voter problems by providing material and non-material resources in exchange of political support.     

Stakeholder influence,government power,and new opportunities for Chinese Internet companies: A multilevel network analysis of cross-sector networks

In recent decades, Chinese Internet companies have experienced exponential growth. As the Internet industry increasingly commends tremendous financial resources, they also face growing stakeholder expectations for corporate social responsibility (CSR) actions. One way through which Chinese Internet companies conduct CSR is by building cross-sectoral collaborations with nonprofit and nongovernmental organizations (NGOs) and governmental agencies. Aiming to understand Internet companies’ strategic relationship building on CSR issues, the researchers drew from stakeholder influence theory and research on a network approach to stakeholder influence, and applied multilevel network analysis to model three networks related to Chinese Internet companies’ CSR collaborations. Specifically, we found that power and urgency are significant predictors of the structure of Internet companies’ cross-sector CSR alliance network. Organizations affiliated or endorsed by the central Chinese government are the most desirable CSR stakeholders. Additionally, the study also revealed that for Internet companies, devoting their attention to Internet-related social issues could increase their desirability as strategic stakeholders from other sectors and among Internet companies.     

Social network analysis for assessing college-aged adults' health: A systematic review

Objective: Social network analysis (SNA) is a useful, emerging method for studying health. College students are especially prone to social influence when it comes to health. This review aimed to identify network variables related to college student health and determine how SNA was used in the literature. Participants: A systematic review of relevant literature was conducted in October 2015. Methods: Studies employing egocentric or whole network analysis to study college student health were included. We used Garrard's Matrix Method to extract data from reviewed articles (n = 15). Results: Drinking, smoking, aggression, homesickness, and stress were predicted by network variables in the reviewed literature. Methodological inconsistencies concerning boundary specification, data collection, nomination limits, and statistical analyses were revealed across studies. Conclusions: Results show the consistent relationship between network variables and college health outcomes, justifying further use of SNA to research college health. Suggestions and considerations for future use of SNA are provided.     

To make and keep friends: The role of health status in adolescent network tie formation and persistence

Health status may shape network structure through network dynamics (tie formation and persistence) and direction (sent and received ties), net of typical network processes. We apply Separable Temporal Exponential Random Graph Models (STERGMs) to National Longitudinal Study of Adolescent to Adult Health survey data (n = 1779) to differentiate how health status shapes network sent and received tie formation and persistence. Results indicate that networks are shaped by withdrawal of adolescents experiencing poor health, highlighting the importance of separating distinct and directed processes of friendship formation and persistence when considering how health relates to adolescent social life.     

The missing link: Social network analysis in migration and transnationalism

The focus on social networks in migration studies marked a significant departure of understanding. Social networks are not only a mechanism through which the migration process is patterned, but they also have broader implications for migrants and non-migrants alike. Despite the fact that the network character of migration processes has long been recognized in migration studies, for a long time, Social Network Analysis has not been applied. Taking this scholarly omission as a starting point, we seek in this special issue to discuss recent research into social networks and migration that use SNA approaches.     

The influence of friends on adolescents’ behavior problems at school: The role of ego,alter and dyadic characteristics

This paper deals with the influence of friends in class on adolescents’ problematic school behavior (i.e. inattention in class and not doing homework). We examine whether this influence is moderated by ego (i.e. the adolescent's indegree), alter (i.e. friends’ indegree) and dyadic characteristics (i.e. friendship reciprocity). Influence processes are analyzed with a stochastic actor-based model (SIENA), while controlling for friendship selection. Using a 4-wave panel dataset, we find that friends influence adolescents’ problematic school behavior. Adolescents with a higher indegree are less likely to be influenced. The influence of friends is not significantly moderated by friends’ indegree and friendship reciprocity.     

Social network analysis of Australian poly-drug trafficking networks: How do drug traffickers manage multiple illicit drugs?

International agencies report rising numbers of drug traffickers who deal in multiple drugs (poly-drug traffickers). This paper explores how product diversification is managed in three Australian poly-drug trafficking syndicates. Networks were constructed using judges’ sentencing comments and social network analysis applied to examine the degree of specialisation, resource flows and management structure (if any). Each syndicate had a clear management structure, but employed a different approach to diversifying including in-house production of multiple products (Syndicate 1) and outsourcing to other syndicates (Syndicate 3). This suggests traffickers will have multiple avenues for product diversification. This may create challenges for their policing.     

Theories of network exchange: Anomalies,desirable properties,and critical networks

The present study evaluates four well-known theories of exchange in networks. In previous research these theories’ predictions were compared for a small set of networks using experimental data. We compared their predictions for all 12,112 networks up to size 8. By comparing these predictions we (i) identified anomalies in theories of network exchange, (ii) investigated to what extent the theories satisfy basic principles of exchange, (iii) identified ‘critical’ networks for which predictions are very different. We conclude that exchange in networks is not yet well understood.     

Longitudinal analysis of personal networks. The case of Argentinean migrants in Spain

This paper discusses and illustrates various approaches for the longitudinal analysis of personal networks (multilevel analysis, regression analysis, and SIENA). We combined the different types of analyses in a study of the changing personal networks of immigrants. Data were obtained from 25 Argentineans in Spain, who were interviewed twice in a 2-year interval. Qualitative interviews were used to estimate the amount of measurement error and to isolate important predictors. Quantitative analyses showed that the persistence of ties was explained by tie strength, network density, and alters’ country of origin and residence. Furthermore, transitivity appeared to be an important tendency, both for acquiring new contacts and for the relationships among alters. At the network level, immigrants’ networks were remarkably stable in composition and structure despite the high turnover. Clustered graphs have been used to illustrate the results. The results are discussed in light of adaptation to the host society.     

And then the internet happened: Thoughts on the future of concept mapping

Over 25 years ago, in the late twentieth century, concept mapping emerged as a mixed method approach to inquiry that enables a group of people to conceptualize their thinking about a specific topic. Since then, the application of concept mapping has spread widely and an easy prediction for the future is that this trend is likely to continue; a more important and greater challenge is to think about the ways in which concept mapping may and should evolve. Discussed here are thoughts about the future of concept mapping including some predictions of likely directions and suggestions for new possibilities. Thoughts on the future are grounded in concept mapping applications that have emerged and gained ground in recent years; these include exploring wicked problems in communities and integrating concept mapping with other methods of inquiry. Thoughts on the future are also grounded in the social and cultural milieu in which we find ourselves at this time. The influence of social media and internet technologies has led to the emergence peer production and crowdsourcing as approaches to co-create information, knowledge, products and services. These tactics may create fertile ground for the further spread of concept mapping. This same collaborative milieu has produced the open software movement which in turn, offers opportunities to enhancing the methodology of concept mapping.     

The development of structure in random networks: an analysis of the effects of increasing network density on five measures of structure

The density of ingroup relations continues to be proposed as an indicator of structural cohesion. Network density is obviously a misleading indicator of structural cohesion when a group has subgroups; in such circumstances, the cohesion may be entirely internal to the subgroups. However, it is plausible that network density is a useful indicator of structural cohesion when it can be assumed that a group lacks subgroups. In order to analyze this possibility, I construct a set of random networks, increase the density of relations in these networks, and observe how the networks' structure develops in terms of five measures. The results show that low densities in large networks may be associated with more structural cohesion than higher densities in smaller networks; it is suggested that in field studies, attempts to control for network size will encounter problems of nonlinearity and heteroscedasticity. I conclude that network density is not a useful indicator of structure and that direct measurement of structure is to be preferred.     

Immigrants and refugees: two sides of the same problem. A linguistic analysis through newspapers and social network in Spain 2006 and 2015

ABSTRACT

The phenomenon of immigration has been studied from diverse perspectives. It is important to note that immigration is common during times of crisis. The reason for the avalanche of immigrants to the Canary Islands (Spain) is because it is the gateway to Europe, and therefore, immigrants wanted to enter from this point. This research is based on the need to linguistically determine the treatment of the phenomenon of immigration in the Spanish press. This analysis is relevant given the arrival of thousands of foreign citizens to the coast of the Canary Islands, first in 2006 and almost a decade later, in 2015 to the south of Europe in another great population movement. This research attempts to study four Spanish newspapers, two from the Canary Islands (El Día and Canarias 7) and two Spanish mainland national newspapers (El País and ABC), the online version of the newspapers and their websites were analyzed beside one of the most important social networks, Twitter. The role of incorporating social networks to immigration discourse is also analyzed. To support the data analysis of this research, the Iramuteq software was used.     

Embedding time in positions: Temporal measures of centrality for social network analysis

Digital data enable researchers to obtain fine-grained temporal information about social interactions. However, positional measures used in social network analysis (e.g., degree centrality, reachability, betweenness) are not well suited to these time-stamped interaction data because they ignore sequence and time of interactions. While new temporal measures have been developed, they consider time and sequence separately. Building on formal algebra, we propose three temporal equivalents to positional network measures that incorporate time and sequence. We demonstrate how these temporal equivalents can be applied to an empirical context and compare the results with their static counterparts. We show that, compared to their temporal counterparts, static measures applied to interaction networks obscure meaningful differences in the way in which individuals accumulate alters over time, conceal potential disconnections in the network by overestimating reachability, and bias the distribution of betweenness centrality, which can affect the identification of key individuals in the network.     

Using social network analysis to complete literature reviews: a new systematic approach for independent researchers to detect and interpret prominent research programs within large collections of relevant literature

ABSTRACT

Literature reviews are required at early stages of a traditional research progression. Many systematic approaches help researchers identify relevant literature. However, there is far less support for interpreting large collections of references. Understanding the evolution of knowledge within a discipline requires an awareness of the collaborative networks from which significant advances originate. Unfortunately, this relational awareness is only acquired after years of professional experience. Therefore, early-career researchers are at a fundamental disadvantage when conducting literature reviews. Social Network Analysis (SNA) can make the interpretation of large collections of literature more manageable. This paper provides a method for generating a co-authorship network from reference lists. The partition of the co-authorship network into communities provides a reviewer with direction to organise literature into meaningful groups. The interpretation of seemingly disparate and entangled research programs is far more manageable when interpreting smaller collections of highly relevant literature.     

Use of a hierarchical deconstruction procedure for the classification of personal networks: Exploring nested groups around you

The deconstruction of personal networks through the iterative elimination of the nodes with the highest betweenness centrality is an effective strategy for describing their structural properties. In this study we show that iterative deconstruction can also serve to classify personal networks into typologies. With longitudinal data from a sample of 69 students, we found that denser networks are more resistant to fragmentation while those organized in defined subgroups usually have a shorter deconstruction process. In addition, the deconstruction strategy allows knowing the hierarchical structure of personal networks, made up of nested subgroups.