Quantitative Network Analysis Research Articles

Quantitative and qualitative approaches to early‐modern networks: The case of George Herbert (1593–1633) and his imitators

AbstractDuring the last two decades, studies of early‐modern networks (whether literary, social, religious, or intellectual) have often used the analytical concept of the network as a convenient metaphor. As a result, studies have not always recognized the benefits of analysing these structures through the methodologies of network analysis. The theoretical approaches and tools of network analysis have been employed in disciplines including social sciences, but only recently have scholars explored the usefulness of such quantitative methodologies within literary‐historical studies. Using a case study of the network of imitators surrounding the devotional poet, George Herbert, this essay reconsiders scholarly approaches to early‐modern literary and intellectual networks. It demonstrates how, when combined with qualitative data from textual analysis, the visual and mathematical tools of quantitative network analysis offer new ways of understanding the configurations of such groups. By moving away from using the term “network” as a metaphor, the essay shows how the perspective provided by quantitative network analysis can complement more familiar scholarly approaches of close textual analysis. Ultimately, its explication and application of these combined qualitative and quantitative research methods challenges scholars to consider how appropriating scientific methods from the field of network analysis can provide answers not only to questions about social relationships but also about questions of aesthetic practices and influence within early‐modern texts.

Finding hidden patterns in ECtHR’s case law

This article is concerned with identifying how contemporary data technology can be used to find and analyse the big amount of case law generated by international courts in a more comprehensive way than that achieved through the traditional manual reading of case law at the core of textbook or doctrinal analysis of judgements. The focus of the article is the European Court of Human Rights (ECtHRs) and its Article 14 + 2 case law, which is studied through the tools of citation network analysis. The resulting findings are then compared to a standard textbook approach in order to show how citation network analysis offers a reliable method in selecting cases for qualitative analysis and drawing information relevant to specific legal issues. The article proposes and eventually advances a new approach to legal research, which integrates quantitative network analysis with qualitative legal (doctrinal) analysis, and shows how this form of analysis enables a study of case law through the recognition of patterns within it that would have otherwise been difficult to identify. Using this approach to advance new insights into the prohibition of discrimination under Article 14 of the European Convention on Human Rights (ECHR), the article ultimately offers a new instrument for scholars and practitioners to put into use when considering the future narrative of discrimination law.

Brittleness analysis and important nodes discovery in large time-evolving complex networks

The brittleness analysis and important nodes detection have been a hot spot in the complex networks. How to get the overall feature of the whole network and how to find out some important nodes are requisites to solve these problems. In this paper, we adopt the trace of the adjacency matrix and the centrality of the complex networks to give a quantitative and qualitative analysis of networks being studied. Results show that the k-shell plays a more important role than the degree centrality and the betweenness in finding important nodes, and it can also be used to give direction on the immunization and maintenance of complex networks.

When Theory Meets Methods: The Naissance of Computer Assisted Corporate Interlock Research

This paper studies the emergence of computer aided network analysis as an example of ‘Mertonian’ multiple discovery. Computer assisted quantitative network analysis emerged around 1970 and was first applied on corporate interlock networks by small groups of researchers in different universities that were independent from each other looking for the right concepts and computer programs to implement graph theory in social analysis. We show how mathematical graph theory provided a toolbox for systematic network analysis and that simultaneously in the Netherlands and the United States this toolbox found an application in the study of corporate power. A historical narrative covers the three main centers where large-scale corporate network analysis emerged: Amsterdam, California and Stony Brook. For each center, we provide a sketch of the people involved, the tools they used, and the motivations that brought them to this topic. Our analysis makes clear that the emergence of computer aided network analysis cannot be understood without taking into account the personal and often political motivations of those who engaged in the first board interlock studies. Insurgent students of political science and sociology pushed for a research agenda on corporate power and found support from scholars who were keen to develop innovative network analysis methods. Hence corporate network analysis became a legitimate field of research.

QMorphoStream: processing tools in QGIS environment for the quantitative geomorphic analysis of watersheds and river networks

The quantitative geomorphic analysis is a powerful tool for the study of geomorphology and landforms, as it provides objective methods to describe the main properties of drainage basins by means of an appropriate set of parameters. Over the last decades, GIS techniques and processing tools have been widely applied to the geomorphic analysis, and specific applications were developed, essentially using commercial software. In the present paper, the first experimental version of QMorphoStream, an originally developed set of processing tools for quantitative geomorphic analysis in QGIS environment, is presented. Besides the obvious advantage in terms of cost reduction, the choice of an open source development environment allowed us to integrate original algorithms with both QGIS built-in functions and processing tools available in the developers’ community.

Calypso: a user-friendly web-server for mining and visualizing microbiome–environment interactions

Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page.Availability and ImplementationThe web-interface is accessible via http://cgenome.net/calypso/. The software is programmed in Java, PERL and R and the source code is available from Zenodo (https://zenodo.org/record/50931). The software is freely available for non-commercial users.Supplementary information Supplementary data are available at Bioinformatics online.

The Effect of the Position of Educational Organizations within the Social Network on Their Collaboration Levels

In this research, it has been aimed to determine the opinions of administrators serving in the public education organizations at the central districts of Sinop on inter-organizations collaboration (collaboration levels). The study, in the descriptive survey model, has been carried out by a mixed research approach where qualitative, quantitative and social network analyses have been used collectively. At the qualitative phase of the research, 36 school administrators have been interviewed, and then the interview inventory has been subjected to content analysis. In the social network analysis phase of the research, the Collaboration Levels Scale developed by the researcher has been applied to 36 school administrators. The obtained data have been analyzed in the UCINET 6.0 software. The density, structural holes, centrality degrees of the responses of the administrators to the items included in the scale have been calculated and network maps have been generated. In the quantitative phase of the research, whether the positional characteristics of the administrators within the organization and network demonstrated variations depending on variables or not has been analyzed with the Mann-Whitney U and Kruskall Wallis Test, since the distribution was not normal. According to the conclusions reached in the study, 36 education institutions have established a collaboration network of 68 actors, including themselves. From these organizations, 39 are education organizations, while 29 are public, private sector and non-governmental organizations. All education organizations at the provincial center have established a collaboration network. There are no isolated organizations. According to the density analysis, 57% of the maximum relations that the organizations could achieve among themselves, has been established. Accordingly, the education organizations have both close and distant connections within the collaboration network. According to the research findings, the education organizations at the provincial center display a structure that is very close within themselves – but closed to the outside. While the areas where the collaboration potential could be used the most in proportion are data sharing, financial resources sharing and administrator opinion exchange, the lowest levels have materialized in working on a common project, institutional health and safety. Among the collaboration levels, from the five levels that are networking, cooperation, coordination, coalition and collaboration, the highest achieved collaboration is the collaboration level. In conclusion, meaningful differentiations have been determined between collaboration subjects and levels, depending on the positions of the organizations within the network (central actor, effectiveness level and betweenness condition). Positions within the network have an impact on the collaboration levels of organizations.

Synergistic Social Network Analysis: A Synergistic Approach to Qualitative and Quantitative Network Analysis

Network analysis in tourism is characterized by a quantitative–qualitative dichotomy, and a more synergistic approach to the field is needed. This article proposes a new network analysis method— synergistic social network analysis (SSNA)—which aims to create such synergies. SSNA involves ways to easily collect both qualitative and quantitative data as well as tools and considerations that build on and develop synergies between qualitative and quantitative perspectives. SSNA is therefore an approach that is more than the sum of its qualitative and quantitative data parts. On a broader level, an important part of SSNA is to create an iterative synergistic way of applying meaning to data, which is not exclusively influenced by traditional qualitative–quantitative epistemologies. SSNA was developed and tested on the basis of a study of six Danish destinations. This application and its evaluation indicate specific methodological and theoretical advantages compared to more traditional dichotomous approaches and demonstrate strong advantages within the study context. Examples of methodological and theoretical advantages include the following: identification of qualitative data collection convergence through quantitative data; quantitative structural perspectives combined with qualitative perspectives on the rationale behind the numbers potentially leading to crystallization; structural tools that can “zoom in” on Central Network Cliques, which enable the researcher to have a qualitative focus on central parts of the network; and quantitative visualizations that create a manageable backdrop on which to base communication of more complex in-depth results to researchers and practitioners. On a more abstract level, the article points to the relevant discussion of how we assimilate knowledge, arguing for a stronger focus on alternatives to the dichotomous qualitative–quantitative approach and for a greater literacy of mixed synergetic methods among tourism researchers.

Extracting microtubule networks from superresolution single-molecule localization microscopy data.

Microtubule filaments form ubiquitous networks that specify spatial organization in cells. However, quantitative analysis of microtubule networks is hampered by their complex architecture, limiting insights into the interplay between their organization and cellular functions. Although superresolution microscopy has greatly facilitated high-resolution imaging of microtubule filaments, extraction of complete filament networks from such data sets is challenging. Here we describe a computational tool for automated retrieval of microtubule filaments from single-molecule-localization-based superresolution microscopy images. We present a user-friendly, graphically interfaced implementation and a quantitative analysis of microtubule network architecture phenotypes in fibroblasts.

Who collaborates and why: Assessment and diagnostic of governance network integration for salmon restoration in Puget Sound, USA

Governance silos are settings in which different organizations work in isolation and avoid sharing information and strategies. Siloes are a fundamental challenge for environmental planning and problem solving, which generally requires collaboration. Siloes can be overcome by creating governance networks. Studying the structure and function of these networks is important for understanding how to create institutional arrangements that can respond to the biophysical dynamics of a specific natural resource system (i.e., social-ecological, or institutional fit). Using the case of salmon restoration in a sub-basin of Puget Sound, USA, we assess network integration, considering three different reasons for network collaborations (i.e., mandated, funded, and shared interest relationships) and analyze how these different collaboration types relate to productivity based on practitioner's assessments. We also illustrate how specific and targeted network interventions might enhance the network. To do so, we use a mixed methods approach that combines quantitative social network analysis (SNA) and qualitative interview analysis. Overall, the sub-basin's governance network is fairly well integrated, but several concerning gaps exist. Funded, mandated, and shared interest relationships lead to different network patterns. Mandated relationships are associated with lower productivity than shared interest relationships, highlighting the benefit of genuine collaboration in collaborative watershed governance. Lastly, quantitative and qualitative data comparisons strengthen recent calls to incorporate geographic space and the role of individual actors versus organizational culture into natural resource governance research using SNA.

Networked Justice: Judges, the Diffusion of Ideas, and Legal Reform Movements in Mexico

AbstractExisting research shows that the ideas of judges shape their behaviour. A natural next question to ask is, where do these ideas come from? Yet, there is little empirical evidence regarding the content and distribution of these ideas and even less evidence regarding the sources of these ideas, especially how ideas transfer or diffuse among judges. In this article, a survey of judges in the Mexican state of Michoacán generates original data on the attitudes and professional ties among these legal elites, and a mixed-methods design examines the diffusion of these attitudes along these ties, sequencing quantitative network analyses and interviews with judges to strengthen causal inferences. The core finding that the social structure of judges influences the attitudes judges hold contributes a valuable analytic complement to scholarship on comparative judicial behaviour, and clarifies our understanding of the role of judicial networks in strengthening democracy and the rule of law.

Nanoscale Imaging of Collagen Gels with Focused Ion Beam Milling and Scanning Electron Microscopy

In vitro polymerized type I collagen hydrogels have been used extensively as a model system for three-dimensional (3D) cell and tissue culture, studies of fibrillogenesis, and investigation of multiscale force transmission within connective tissues. The nanoscale organization of collagen fibrils plays an essential role in the mechanics of these gels and emergent cellular behavior in culture, yet quantifying 3D structure with nanoscale resolution to fully characterize fibril organization remains a significant technical challenge. In this study, we demonstrate that a new imaging modality, focused ion beam scanning electron microscopy (FIB-SEM), can be used to generate 3D image datasets for visualizing and quantifying complex nanoscale organization and morphometry in collagen gels. We polymerized gels at a number of concentrations and conditions commonly used for in vitro models, stained and embedded the samples, and performed FIB-SEM imaging. The resulting image data had a voxel size of 25 nm, which is the highest resolution 3D data of a collagen fibril network ever obtained for collagen gels. This resolution was essential for discerning individual fibrils, fibril paths, and their branching and grouping. The resulting volumetric images revealed that polymerization conditions have a significant impact on the complex fibril morphology of the gels. We segmented the fibril network and demonstrated that individual collagen fibrils can be tracked in 3D space, providing quantitative analysis of network descriptors such as fibril diameter distribution, length, branch points, and fibril aggregations. FIB-SEM 3D reconstructions showed considerably less lateral grouping and overlap of fibrils than standard 2D SEM images, likely due to artifacts in SEM introduced by dehydration. This study demonstrates the utility of FIB-SEM for 3D imaging of collagen gels and quantitative analysis of 3D fibril networks. We anticipate that the method will see application in future studies of structure-function relationships in collagen gels as well as native collagenous tissues.

The method of leader's overthrow in networks based on Shapley value

Quantitative methods for leaders' detection and overthrow are useful tools for decision-making in many real-life social networks. In the given research, we present algorithms that detect and overthrow the most influential node to the weaker leadership positions following the greedy method in terms of structural modifications. We employ the concept of Shapley value from the area of cooperative game theory to measure a node's leadership and to develop the leader's overthrow algorithms. Specifically, we introduce a quantitative approach to analyze prospective structural modifications in social networks to make the initially identified network leader less influential. The resulting mechanism is based on the symbiosis of game-theoretic and algorithmic concepts. It presents a useful tool for the technical analysis of the primary structural data in the initial steps of multifaceted quantitative network analysis where the raw data (i.e., linkages) is frequently the only knowledge about interrelations in social networks.

Friendship networks of the foreign students in schools of Barcelona: impact of class grouping on intercultural relationships

This paper account for the relational dynamics that take place in high schools: the interculturality level in the networks of foreign students. Relational networks are characterized by their composition based on origin, identifying those exclusively consisting of native students, those in which only foreign students interact, and the intercultural networks themselves, where native and foreign students coexist. At this stage, I analyse the organizational factors that impede the integration of immigrant students in relational networks with presence of native students, as well as other factors that support the establishment of such networks. Specifically, the analysis focuses on how the organization of school classrooms impact the establishment of more or less intercultural relational networks. In short, there is one concern that motivate this paper: the existence of school dynamics that enhance ethnic ghettoization within schools and, therefore, impede social integration.This research includes the analysis of all students enrolled in the last year of compulsory education (16 years-old) of eight high schools in the Metropolitan Area of Barcelona (for a total of 664 students from 28 classes). The analytical exploitation is based on a quantitative approach and network analysis (UCINET and Netdraw).Main findings show that the identification of the classrooms with certain ability levels seems to imply a greater barrier between classrooms, which can lead to a greater or lower relational cohesion within the class, according to school organitzation. By contrast, ability levels do not have a direct impact on the degree of intercultural contact; although they do exert a significant influence, defining the possibilities of contact between groups.

Comprehensive In Situ Analysis of Arteriolar Network Geometry and Topology in Rat Gluteus Maximus Muscle.

To provide detailed geometric and topological descriptions of the rat gluteus maximus arteriolar network, and to measure the distribution of diameters and lengths as well as their associated variability within and between networks. Complete arteriolar networks arising from feed artery (inferior gluteal artery) to terminal branches were imaged under baseline conditions, using IVVM. Photomontages of complete networks were assembled and evaluated offline for measurements of geometry and topology. Single-line (skeletonized) tracings of the networks were made for fractal analysis. Diameters and lengths decreased with increasing topological order (centrifugal), while number of elements increased with increasing order. Horton's laws were shown to be valid within the arteriolar networks of the rat GM. Inter-network variability in diameter (~5-22%) and length (~17-30%) at each order was generally lower than the corresponding intra-network variability in diameter (~10-48%) and length (~39-106%). Data presented in this study provide crucial quantitative analysis of complete arteriolar networks within healthy skeletal muscle, and may serve as ideal experimental inputs for future theoretical studies of skeletal muscle microvascular structure and function.

Predicting the cell death responsiveness and sensitization of glioma cells to TRAIL and temozolomide.

Genotoxic chemotherapy with temozolomide (TMZ) is a mainstay of treatment for glioblastoma (GBM); however, at best, TMZ provides only modest survival benefit to a subset of patients. Recent insight into the heterogeneous nature of GBM suggests a more personalized approach to treatment may be necessary to overcome cancer drug resistance and improve patient care. These include novel therapies that can be used both alone and with TMZ to selectively reactivate apoptosis within malignant cells. For this approach to work, reliable molecular signatures that can accurately predict treatment responsiveness need to be identified first. Here, we describe the first proof-of-principle study that merges quantitative protein-based analysis of apoptosis signaling networks with data- and knowledge-driven mathematical systems modeling to predict treatment responsiveness of GBM cell lines to various apoptosis-inducing stimuli. These include monotherapies with TMZ and TRAIL, which activate the intrinsic and extrinsic apoptosis pathways, respectively, as well as combination therapies of TMZ+TRAIL. We also successfully employed this approach to predict whether individual GBM cell lines could be sensitized to TMZ or TRAIL via the selective targeting of Bcl-2/Bcl-xL proteins with ABT-737. Our findings suggest that systems biology-based approaches could assist in personalizing treatment decisions in GBM to optimize cell death induction.

Weak network efficiency in young children with Autism Spectrum Disorder: Evidence from a functional near-infrared spectroscopy study

Functional near infrared spectroscopy (fNIRS) is particularly suited for the young population and ecological measurement. However, thus far, not enough effort has been given to the clinical diagnosis of young children with Autism Spectrum Disorder (ASD) by using fNIRS. The current study provided some insights into the quantitative analysis of functional networks in young children (ages 4.8–8.0years old) with and without ASD and, in particular, investigated the network efficiency and lobe-level connectivity of their functional networks while watching a cartoon. The main results included that: (i) Weak network efficiency was observed in young children with ASD, even for a wide range of threshold for the binarization of functional networks; (ii) A maximum classification accuracy rate of 83.3% was obtained for all participants by using the k-means clustering method with network efficiencies as the feature parameters; and (iii) Weak lobe-level inter-region connections were uncovered in the right prefrontal cortex, including its linkages with the left prefrontal cortex and the bilateral temporal cortex. Such results indicate that the right prefrontal cortex might make a major contribution to the psychopathology of young children with ASD at the functional network architecture level, and at the functional lobe-connectivity level, respectively.

The structuring of information through search: sorting waste with Google

Purpose– The purpose of this paper is to explore informational structures producing and organising the construction of waste sorting in Sweden. It shows how the issue is constructed by it being searched for in Google and how this contributes to the specific informational texture of waste sorting in Sweden. It is guided by the following questions: who are the main actors and which are the central topics featuring in Google results on popular, suggested searches for waste sorting in Sweden? What do the link relations between these tell the author about the issue space that is formed around waste sorting in Sweden? How is the construction of the notions of waste sorting and waste shaped in the information available through Google’s features for related and other relevant searches?Design/methodology/approach– Waste sorting is discussed as a practice structured along moral rules and as a classification exercise. The study brings together two types of material, results from searches carried out in Google and lists of Google query suggestions for relevant search terms. These are analysed with a mixed method approach, uniting quantitative network analysis and qualitative content analysis of query suggestions. A sociomaterial approach theoretically grounds the analysis.Findings– Waste sorting in Sweden emerges as an issue that is characterised by dense networks of rules and regulation, focused in public authorities and government agencies, which in turn address consumers, waste management businesses and other authorities. Search engine use and waste sorting in Sweden are shown to be joined together in various mundane everyday life practices and practices of governance that become visible through the search engine in form of search results and suggested searches. The search engine is shown to work as a fluid classification system, which is also created and shaped by its use.Originality/value– The study offers a novel methodological approach to studying the informational structures of an issue and of its shaping through it being searched for. The sociomaterially grounded analysis of Google as a fluid classification system is original.

Migrants in the periphery: migrant organisations and their networks

ABSTRACTPoverty rates among people with a foreign background in Europe are increasing exponentially. Literature shows that migrant organisations can play a central role to combat poverty. However, scientific evidence on their specific role in the provision of service towards people in poverty is lacking [Dierckx, et al. (2009); Heyse, 2008; Spencer, & Cooper (2006, January 10)]. We consider migrant organisations as a particular type of civil society organisations (CSOs) providing services or activities to a specific group of migrants. It is argued that these organisations must collaborate with different service organisations such as public service agencies and a variety of other CSOs providing crucial services such as financial and material aid. We used a mixed method social network analysis to investigate the networks among migrant organisations, public services and CSOs. We conduct a quantitative social network analysis in a deprived neighbourhood in Antwerp, Belgium. The findings show a lack of collaboration between migrant organisations, public services and other CSOs. Qualitative research is used to explain the lack of collaboration in this network. Our findings detect crucial challenges that must be overcome when bridging the gap between migrant organisations and public services or CSOs, in order to achieve poverty alleviation among migrants.

Host specificity in a diverse Neotropical tick community: an assessment using quantitative network analysis and host phylogeny.

BackgroundHost specificity is a fundamental determinant of tick population and pathogen transmission dynamics, and therefore has important implications for human health. Tick host specificity is expected to be particularly high in the tropics, where communities of ticks, hosts and pathogens are most diverse. Yet the degree to which tropical tick species are host-specific remains poorly understood. Combining new field data with published records, we assessed the specificity of tick-host associations in Panama, a diverse Neotropical region.MethodsThe resulting dataset includes 5,298 adult ticks belonging to 41 species of eight genera that were directly collected from 68 vertebrate host species of 17 orders. We considered three important aspects of tick host specificity: (i) the relative ecological importance of each host species (structural specificity); (ii) relatedness among host species (phylogenetic specificity); and (iii) spatial scale-dependence of tick-host relationships (geographical specificity). Applying quantitative network analyses and phylogenetic tools with null model comparisons, we assessed the structural and phylogenetic specificity across three spatial scales, ranging from central Panama to countrywide. Further, we tested whether species-rich tick genera parasitized a wider variety of hosts than species-poor genera, as expected when ticks specialize on different host species.ResultsMost tick species showed high structural and/or phylogenetic specificity in the adult stage. However, after correcting for sampling effort, we found little support for geographical specificity. Across the three scales, adult ticks tended to be specific to a limited number of host species that were phylogenetically closely related. These host species in turn, were parasitized by tick species from distinct genera, suggesting switching among distantly related hosts is common at evolutionary timescales. Further, there was a strong positive relationship between the taxonomic richness of the tick genera and that of their hosts, consistent with distinct tick species being relatively specific to different host species.ConclusionsOur results indicate that in the adult stage, most ticks in the diverse Neotropical community studied are host specialists. This contrasts with earlier assessments, but agrees with findings from other host-parasite systems. High host specificity in adult ticks implies high susceptibility to local tick-host co-extirpation, limited ability to colonize new habitats and limited potential for interspecific pathogen transmission.Electronic supplementary materialThe online version of this article (doi:10.1186/s13071-016-1655-6) contains supplementary material, which is available to authorized users.