Affiliation Networks Research Articles

Ecological Influences on Network Tie Dissolution in the Evolution of Affiliation Networks in the International Communication Association, 2009–2015

AbstractThis study examined the influences of ecological factors on the dissolution of affiliation ties in the International Communication Association (ICA). The affiliation network in this study represented the connections between ICA members and ICA divisions and interest groups. Guided by insights from organizational ecology and network theory, this research used a multilevel discrete-time event history analysis to test how ecological factors influenced active ICA members’ decisions to drop affiliation ties. An empirical analysis was conducted using a longitudinal sample of 1,282 active members and 23 divisions and interest groups from 2009 to 2015. The results showed that the likelihood of tie dissolution was significantly constrained by the length of an individual’s organizational membership, the division or interest group’s fuzzy density (generally considered as a proxy for legitimacy perceptions), and the group’s contrast (one measure of the level of clarity vs ambiguity of a group’s identity). Theoretical and practical implications are discussed.

Qualitative Study of Interprofessional Collaboration in Radiation Oncology Clinics: Is There a Need for Further Education?

Interprofessional education (IPE) is gaining recognition as a means of improving health care delivery and patient outcomes. A primary goal of IPE is improved interprofessional collaboration (IPC). The multidisciplinary team in the radiation oncology clinic requires effective IPC for optimal delivery of radiation therapy. However, there are limited data on IPE and IPC in radiation oncology. This qualitative study aims to characterize IPC in radiation oncology. Semistructured phone interviews were performed from June to August 2019 with radiation oncologists, nurses, dosimetrists, radiation therapists, medical physicists, and medical students across a single academic medical center and affiliated network sites. Interviews were recorded, de-identified, and transcribed verbatim. Resulting transcripts were analyzed using thematic analysis. Seventeen interviews were performed with 4 radiation oncologists, 2 nurses, 2 dosimetrists, 4 radiation therapists, 2 medical physicists, and 3 medical students. Thematic analysis identified 4 themes: (1) management of the radiation oncology clinic, (2) potential impact of interprofessional training in radiation oncology, (3) current climate of interprofessional education in radiation oncology, and (4) creating an interprofessional training program in radiation oncology. Each theme elicited between 2 and 7 subthemes. From the analytical themes that emerged, it is hypothesized that misunderstanding professionals' roles can lead to communication breakdown, which creates less efficient clinic management and disorganized patient care. Although other medical professionals shadow physicians during their training, physicians are not learning about other professions in the same way. Interviewees from each professional category recommend a formal shadowing program for radiation oncology trainees at the medical student or resident level. Having structured opportunities for IPE is important given competing demands of learners during medical student rotations and residency. This study suggests an unmet need for exposure of radiation oncology medical trainees to IPE with the ultimate goal of improving IPC in the radiation oncology clinic.

Inference in a probit model for affiliation networks

Affiliation network is a two-mode social network composed of two different groups of nodes (a group of actors and a group of social events) and the edge between nodes to represent the affiliation relationship between actors and social events. Although a number of statistical models are proposed to analyze affiliation networks, the probit distribution to model the degree heterogeneity of the affiliation networks are still unknown or have not been properly explored. In this paper, we use the probit distribution to model the degree heterogeneity of the affiliation networks and establish the uniform consistency and the asymptotic normality of the moment estimator when the number of actors and events both go to infinity. Simulation studies and a real data example demonstrate our theoretical results.

Identifying Mild Hepatic Encephalopathy Based on Multi-Layer Modular Algorithm and Machine Learning.

Hepatic encephalopathy (HE) is a neurocognitive dysfunction based on metabolic disorders caused by severe liver disease, which has a high one-year mortality. Mild hepatic encephalopathy (MHE) has a high risk of converting to overt HE, and thus the accurate identification of MHE from cirrhosis with no HE (noHE) is of great significance in reducing mortality. Previously, most studies focused on studying abnormality in the static brain networks of MHE to find biomarkers. In this study, we aimed to use multi-layer modular algorithm to study abnormality in dynamic graph properties of brain network in MHE patients and construct a machine learning model to identify individual MHE from noHE. Here, a time length of 500-second resting-state functional MRI data were collected from 41 healthy subjects, 32 noHE patients and 30 MHE patients. Multi-layer modular algorithm was performed on dynamic brain functional connectivity graph. The connection-stability score was used to characterize the loyalty in each brain network module. Nodal flexibility, cohesion and disjointness were calculated to describe how the node changes the network affiliation across time. Results show that significant differences between MHE and noHE were found merely in nodal disjointness in higher cognitive network modules (ventral attention, fronto-parietal, default mode networks) and these abnormalities were associated with the decline in patients’ attention and visual memory function evaluated by Digit Symbol Test. Finally, feature extraction from node disjointness with the support vector machine classifier showed an accuracy of 88.71% in discrimination of MHE from noHE, which was verified by different window sizes, modular partition parameters and machine learning parameters. All these results show that abnormal nodal disjointness in higher cognitive networks during brain network evolution can be seemed as a biomarker for identification of MHE, which help us understand the disease mechanism of MHE at a fine scale.

The Janus face of bank geographic complexity

We study the relationship between bank geographic complexity and risk using a unique dataset of 96 global bank holding companies (BHCs) over 2008–2016. From data on the affiliate network of internationally active banking entities, we construct a measure of geographic coverage and complexity for each BHC. We find that higher geographic complexity heightens banks’ capacity to absorb local economic shocks, reducing their risk. However, higher geographic complexity can also help banks soften the impact of prudential regulation, increasing their risk. Bank geographic complexity therefore has a Janus face, decreasing some but increasing other aspects of bank risk.

Organizational Closeness Centralities of Workflow-Supported Performer-to-Activity Affiliation Networks

A workflow model specifies execution sequences of the associated activities and their affiliated relationships with roles, performers, invoked-applications, and relevant data. These affiliated relationships exhibit a series of valuable human-centered organizational knowledge and are utilized for exploring human resource's work patterns. This paper focuses not only on a specific type of affiliated relationships between performers and activities, in particular, which forms a performer-to-activity affiliation network, but also on a specific type of analysis techniques, which builds a closeness centrality measurement approach for quantifying the degrees of farnesses between performers as well as between activities. In other words, this paper investigates a series of formal approaches for building organizational closeness centrality measurement techniques on the specific type of affiliation networks. The investigation mainly deploys two types of algorithmic formalisms along with an operational example, which are measuring performer-centered organizational closeness centralities and activity-centered organizational closeness centralities, respectively. In order to validate the deployed algorithmic equations, the paper carries out a couple of operational experiments; One is on an ICN-based workflow package and the other is on a discovered workflow model mined from a dataset of workflow event logs. Summarily, this paper devises a series of algorithms and equations for measuring closeness centralities of activities, verify the devised algorithms and their related equations along with operational examples, and discuss the ultimate implications of these analysis techniques of organizational closeness centrality measurements as the performer-to-activity affiliation networking knowledge in workflow-supported organizations.

Interpreting Nestedness and Modularity Structures in Affiliation Networks: An Application in Knowledge Networks Formed by Software Project Teams

An understanding of the knowledge creation and diffusion process in the organizational context is extremely relevant. Because from this understanding, organizations can restructure processes, reorient teams and implement methodologies to assist in the construction of an evolutionary process of knowledge creation and diffusion aimed at sustainable growth and innovation. The theory of complex social networks has been applied in several fields to help understand organizational cognitive processes. However, these approaches still insipiently consider the analysis of the nestedness and modularity of the studied networks. In this article, we presented an approach that sought to identify patterns of nestedness and modularity in networks of affiliation of people in projects in the organizational context. The study sought to identify these patterns in affiliation networks in a public organization providing information technology services in the period from 2006 to 2013. The detection of these patterns was performed using the NODF (Nestedness metric based on Overlap and Decreasing Fill) algorithm described by [1]. The nestedness and modularity metrics can influence patterns of knowledge creation and diffusion in formal and informal networks constituted for the execution of projects in organizations. This study showed that the network structures of the organization during the study period presented a high degree of nestedness, and it was possible to identify combined structures of nestedness and modularity.

How College Makes Liberals (or Conservatives)

The author examines the role of affiliation networks in shaping the political identities of students in college, using panel survey data from a case study of a predominantly liberal institution, tracking students’ political identities and affiliation memberships throughout the course of college. Although there was some self-selection into politically homophilous student organizations and majors, the extent of political sorting was relatively low, which resulted in considerable political heterogeneity in the affiliation networks. During the course of college, students’ political identities shifted in both liberal and conservative directions. Results from hierarchical multinomial logistic regressions suggest that identity transitions were driven by both the political composition of peer networks and influences outside the educational institution, such as family and prior socialization. This research underscores the importance of considering network stratification and individual contexts for understanding heterogeneous influences of seemingly uniform institutional settings.

Dynamics of Knowledge in Software Project Development Environments: An Approach Using Affiliation Networks

Dynamics of Knowledge in Software Project Development Environments: An Approach Using Affiliation Networks

An Application of Social Network Analysis to Focus Group Discussions: Unobserved Interaction Between Participants and Discussion Topics

While focus group discussions have become popular across the communication research field, some researchers have pointed out the importance of studying group interactions within focus groups. However, most researchers used a qualitative approach and mostly explored the interaction between participants or between participants and the moderator. This study claimed there might be a third and unobservable interaction that occurs between participants and structured discussion topics. An affiliation network in social network analysis was applied to investigate this phenomenon among eight groups of existing focus group conversations. By affiliation network data and network visualization, this study demonstrated diverse structures between groups. The interaction between participants and discussion topics was significantly different between at least two groups. The results showed that social network analysis could be a tool to help examine focus group interactions from qualitative data, and the interaction between participants and discussion topics could be a potential third interaction in focus group studies. This study is limited by comparing the mean difference between groups. Future research may examine short- and long-term causal effects of group interaction on participation or attitude changes after focus group discussions.

The Role of COVID-19 in Transitioning to a Better Pediatric Payment Model

* Abbreviations: COVID-19 — : coronavirus disease 2019 PMPM — : per member per month The coronavirus disease 2019 (COVID-19) pandemic has quickly impacted health care systems and especially primary care pediatricians. Although fortunately cases of severe COVID-19 and the associated multisystem inflammatory syndrome in children have been rare, the disruptions caused by the COVID-19 pandemic have exposed the financial vulnerability of independent pediatric practices that rely primarily on fee-for-service revenue. Social distancing and stay-at-home advisories have led to the cancellation of routine well-child and follow-up visits for many children and young adults nationwide, as evidenced by the steep drop in childhood vaccines since March.1 Furthermore, social distancing has led to a significant reduction in the incidence of common infections and playground and sports injuries, further diminishing the need for office visits.2 And, even when children do become ill or injured, parents fear exposing their children to infection by bringing them for care during the pandemic. Yet although children have been relatively spared from the brunt of direct health effects of COVID-19, social isolation and lack of school attendance have placed them at increased risk for mental health disorders, missed screenings for lead poisoning, poor nutrition and/or exercise habits, and undetected child abuse, which are situations that call for a strengthening of the primary care infrastructure to assure children’s health needs are met. In our own affiliated primary care network, in-person visits initially fell by ∼75% after statewide … Address correspondence to Michael A. Lee, MD, MBA, Department of Accountable Care and Clinical Integration, Boston Children’s Hospital, 300 Longwood Ave, Mailstop 3196, Boston, MA 02115. E-mail: michael.lee2{at}childrens.harvard.edu

An Investigation on the Use of Facebook Communities for Emotional Support by Nigerian Women

There exists relationship between low emotional support and poor physical and mental health outcomes and increase mortality risk. Increased emotional support is said to be a protective factor for vulnerable populations. An effective way of increasing emotional support is through social network affiliation. This study focused on the use of Facebook communities for emotional support by Nigerian women. The study has three (3) objectives: To discover the importance of online support communities in women’s lives by ascertaining how the lives of women in Facebook communities are significantly affected; establish if Facebook communities can contribute to the growth and development of women; determine if relationships can be established on the group and reinforced outside Facebook community. The research adopts the ecological systems theory for theoretical guide, while in-depth interview was used as methodology. Fifteen (15) participants were drawn as sample through snow-ball sample technique. These participants were reached through two interlocutors who agreed to participate in the research. The study gathered that the common stories posted in the group were that of abuse; all participants agreed that abuse was a fundamental issue that needed to be tackled. Some participants advocated for more posts about self-development and economic opportunities. The study concludes that online communities can serve as safe-spaces for women seeking support from their fellow women. The study recommends that the key to complete women’s emancipation lies in their economic freedom. It is nearly impossible for women to achieve full freedom if their economic power is still largely dependent on the men who are committed to dominating them.

Blackouts in Retransmission Consent Negotiations: Empirical Analysis of Factors Predicting Their Frequency and Duration

This paper examines the factors predicting the frequency and duration of local broadcast television blackouts by Multichannel Video Programming Distributors (MVPDs), as a consequence of breakdowns in retransmission consent negotiations. Using a database of 372 retransmission agreements executed between 2011-2018, the paper uses a binomial logistic regression to identify the factors predicting blackouts, and ordinary least squares (OLS) regression for the duration. It finds the broadcasters’ network affiliations, the number of cable subscribers affected by a retransmission agreement, and a time trend to be the most significant predictors.

Application Of Graph Theory To Find Optimal Path And Minimized Time For The Transportation Problem

Graph theory is used to model many types of relations and process in real world network systems such as internet, power grids, telephone, transportation, affiliation networks, food webs, electricity, water and so on.

Heritage Values and Rehabilitation: Architectural Intervention in the Archaeological Museum of Seville (Spain)

The present investigation examines the role of museum buildings in their consideration as heritage institutions. A particular interest in rehabilitation processes and conversion of international exhibition pavilions into museums will be assessed. The Archaeological Museum of Seville will be taken as a case study. The Ibero-American Exhibition of Seville (1929) was a paramount event in the city, with a vast development of the southern area of the city as well as a display of flourishing regionalist architecture. Its powerful image has transcended from this temporary event, embracing relevant institutions over decades, such as the Archeological Museum. Plus, historical preservation has enhanced its heritage value. Within the grounds of the historic María Luisa Park, the museum has undergone a remarkable evolution as an institution that requires a new relationship with its building, together with an adequation to new museological perspectives. During the lifetime of the museum, the former exhibition pavilion has experienced a succession of rehabilitation processes in the 20th century, always searching for a continuity with the concept of the original building. However, the evolution of the institution faces new challenges for the 21st century: display of the collection, technological issues, public and community services, network affiliation, etc. A series of cultural heritage protection measures that affect the property and its collections, its immediate environment, and the urban environment in which it is located, condition the building and its urban context. Nowadays, a new architectural intervention is in process, with the main goal of putting together all these requirements. The project also deals with the production of a new architecture of representation, respecting and rehabilitating the original regionalist building but also creating a contemporary image for the institution. The relevance of the museum, together with its urban role, make the Archeological Museum of Seville an important agent of cultural requalification. In conclusion, this paper will show how urban culture has been renewed, experiencing a decisive transformation of public spaces and cultural facilities, for leisure, education, or tourism. A new reconsideration of the Cultural Property in question is an experience that can be extrapolated to other museum experiences that emerged in the 20th century and that are currently undergoing a comprehensive reexamination.

Combining social network and data envelopment analysis: A proposal for a Selection Employment Contracts Effectiveness index in healthcare network applications

Combining social network analysis (SNA) and data envelopment analysis (DEA) techniques is a recent and relevant trend in the literature. However, although other works have integrated these techniques, none have done so in the way proposed in this study. Seven generic stages were defined to combine these methods and create a new indicator, the Selection Employment Contracts Effectiveness Index, which measures the extent to which the employment contracts selection by a professional is effectively converted into influential social network positioning. Utilising three DEA models (CCR, BCC and RAM with inverted frontier) and choosing a normalization criterion (no normalization, normalization by size, or normalization by size with sensibility factor), this index can be broken down in terms of the quality and quantity of employment contracts selected. These indices were used in a Brazilian healthcare network to demonstrate that: (a) the number of optimal employment contracts of physicians in the network is one; and (b) the Adjusted Selection Employment Contracts Effectiveness Index by quality (ASECEql) correlates negatively with the workload and the number of physician's specialties. This work offers a new means of analysing the nodes in an affiliation network.

Receipt

Tip decomposition is a crucial kernel for mining dense subgraphs in bipartite networks, with applications in spam detection, analysis of affiliation networks etc. It creates a hierarchy of vertex-induced subgraphs with varying densities determined by the participation of vertices in butterflies (2, 2-bicliques). To build the hierarchy, existing algorithms iteratively follow a delete-update (peeling) process: deleting vertices with the minimum number of butterflies and correspondingly updating the butterfly count of their 2-hop neighbors. The need to explore 2-hop neighborhood renders tip-decomposition computationally very expensive. Furthermore, the inherent sequentiality in peeling only minimum butterfly vertices makes derived parallel algorithms prone to heavy synchronization. In this paper, we propose a novel parallel tip-decomposition algorithm - REfine CoarsE-grained Independent Tasks (RECEIPT) that relaxes the peeling order restrictions by partitioning the vertices into multiple independent subsets that can be concurrently peeled. This enables RECEIPT to simultaneously achieve a high degree of parallelism and dramatic reduction in synchronizations. Further, RECEIPT employs a hybrid peeling strategy along with other optimizations that drastically reduce the amount of wedge exploration and execution time. We perform detailed experimental evaluation of RECEIPT on a shared-memory multicore server. It can process some of the largest publicly available bipartite datasets orders of magnitude faster than the state-of-the-art algorithms - achieving up to 1100× and 64× reduction in the number of thread synchronizations and traversed wedges, respectively. Using 36 threads, RECEIPT can provide up to 17.1× self-relative speedup.

Qualitative Study of Interprofessional Collaboration in Radiation Oncology Clinics: Is There a Need for Interprofessional Education?

Interprofessional education (IPE) is gaining recognition as a means of improving healthcare delivery and patient outcomes. A primary goal of IPE is improved interprofessional collaboration (IPC). The multidisciplinary team in the radiation oncology clinic requires effective IPC for optimal delivery of radiotherapy. However, there are limited data on IPE and IPC in radiation oncology. This qualitative study aims to characterize IPC and IPE in radiation oncology. Semi-structured phone interviews with radiation oncologists, nurses, dosimetrists, radiation therapists, medical physicists, and medical students across a single academic medical center and affiliated network sites were performed from June to August 2019. Interviews were recorded, de-identified, and transcribed verbatim. Resulting transcripts were analyzed using constructivist grounded theory methodology. Seventeen interviews were performed with four radiation oncologists, two nurses, two dosimetrists, four radiation therapists, two medical physicists, and three medical students. Grounded theory analysis identified four themes: 1) Management of the radiation oncology clinic, 2) Current climate of interprofessional education in radiation oncology, 3) Potential impact of interprofessional training in radiation oncology, and 4) Creating an interprofessional training program in radiation oncology. Each theme elicited between 2-7 subthemes. From the analytical themes that emerged, it is hypothesized that misunderstanding radiation oncology health professionals’ roles can lead to communication breakdown, which creates less efficient clinic management and disorganized patient care. While other radiation oncology professionals shadow physicians during their training, physicians are not learning about these professions in the same way. Interviewees from each professional category recommend a formal shadowing program for radiation oncology medical trainees at the resident or medical student level. Having structured opportunities for IPE is important given competing demands of learners during residency and medical student rotations. This study suggests an unmet need for exposure of radiation oncology medical trainees to IPE with the ultimate goal of improving IPC in the radiation oncology clinic.

Who Joins the Franchise, Affiliation Model of Hospital Networks? An Analysis of Hospital and Market Characteristics of Members.

Joining nonownership based, organization-driven networks and alliances is a common strategy for hospitals to pursue yet little is known about what types of hospitals join these collaborations, due in part to challenges in identifying members. One novel network form that has recently emerged, and made identification feasible, is franchise-like "affiliation networks" in which affiliate hospitals pay an annual membership fee that allows access to the clinical expertise and resources of high-status, nationally ranked sponsor hospitals. Affiliation networks and their members publicize affiliation. Using 2006-2015 data on United States' hospitals, we find hospitals with higher patient acuity, teaching hospitals, and hospitals located in areas of higher utilization intensity were more likely to join an affiliation network. Joining affiliation networks does not appear to be in response to highly competitive markets because hospitals in less competitive environments are more likely to join and hospitals with higher net incomes are more likely to join.

Spatial Design of Guest Feeding Programs and Their Effects on Giraffe Participation and Social Interactions

ABSTRACT Guest-animal feeding programs (GFPs) in zoological institutions aim to foster human-animal connections. The growing establishment of animal welfare science emphasizes the assessment of GFPs as permanent environmental inputs to habitats that require analysis of behavioral output. This study assessed the role of space allocation on giraffe participation and interactions in GFPs in two Florida zoos. Analysis of social structure indicates that centrality and influence from affiliative network on exhibit shape sharing interactions at GFPs under varying management protocols and designs. Findings suggest that interactions and significant ties among conspecifics are context and potentially temporally dependent. We propose the use of multiple guest engagement stations to maximize space and facilitate feeding opportunities for central and peripheral members. This proposed shift would provide variable feeding opportunities that represent group composition following ecological theory while maximizing points of guest engagement. Results indicate that increasing space allocation for GFPs increased feeding bout length for individuals, percent of time sharing among conspecifics, and reduced average rate of displacement/minute. Cross-institutional comparisons indicate that guest programs with more space allocation have lower rates of conspecific displacement.