Animating the development of Social Networks over time using a dynamic extension of multidimensional scaling

The animation of network visualizations poses technical and theoretical challenges. Rather stable patterns are required before the mental map enables a user to make inferences over time. In order to enhance stability, we developed an extension of stress-minimization with developments over time. This dynamic layouter is no longer based on linear interpolation between independent static visualizations, but change over time is used as a parameter in the optimization. Because of our focus on structural change versus stability the attention is shifted from the relational graph to the latent eigenvectors of matrices. The approach is illustrated with animations for the journal citation environments of Social Networks, the (co-)author networks in the carrying community of this journal, and the topical development using relations among its title words. Our results are also compared with animations based on PajekToSVGAnim and SoNIA

Social Networks and Transnational Social Fields: A Review of Quantitative and Mixed-Methods Approaches

Ashton Verdery acknowledges assistance provided by the Population Research Institute, which is supported by an infrastructure grant by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24-HD041025), and the Institute for CyberScience at Penn State University.Scholars of transnationalism have argued that migrants create transnational social fields or spaces that connect their place of origin to destination areas. Despite the centrality that social networks have in the definition of these concepts, quantitative and mixed-methods social network research is rare in research on transnationalism. This situation, however, has changed over the last decade, and the transnational social networks of migrants have been studied with multiple methodologies. So far, this literature has not been systematically evaluated. With the aim of taking stock of this research, we classify the literature into four types of approaches (individual, household, dyad/small set, and community) and review their distinct contributions regarding the functioning of immigrants' transnational networks, as well as the relative strengths and limitations of each approach. On the basis of our analysis, we discuss pathways for future investigation

EUSN 2021 Book of Abstracts, Fifth European Conference on Social Networks

Book of abstract of the fifth European conference on Social Networks EUSN 202

Academic Networking Face-to-Face: what it Looks Like and what it Can Tell Us about Research Collaboration

Este trabajo se basa en las herramientas de análisis de la conversación y la teoría de redes para investigar cómo se realizan las redes académicas en la interacción cara a cara en presentaciones científicas. Un análisis de 176 exposiciones presentadas a un público interdisciplinario de investigadores por pares al principio de su carrera participando en un programa postdoctoral europeo reveló cinco funciones de mencionar miembros individuales del público (procesal, anclaje deíctico de ejemplos, contextualizar, establecer co-afiliación, ‘cazar’ colaboración investigadora); también se destacan patrones típicos de encadenamiento intertextual. El estudio documenta una variación en el uso de menciones individuales por estudiosos de diversas disciplinas; también muestra que el orden en que los investigadores exponen influye en las posibilidades de ser mencionado por otros. Un cuestionario de seguimiento diseñado para sondear cómo se relacionan los patrones identificados con colaboración posterior muestra que los investigadores que mencionaron otros eran más propensos a mantener contacto y colaborar como co-autores con miembros de su cohorte. Implicaciones del estudio para una mejor comprensión de la dinámica de colaboración de investigación y capacitación para la práctica académica serán tratadas brevemente.This paper draws on the tools of conversation analysis and network theory to investigate how academic networking takes place face-to-face in academic presentations. An analysis of 176 presentations made to interdisciplinary peer audiences by early-career scholars participating in an EU-funded postdoctoral programme reveals five functions of mentioning individual audience members (procedural, deictic anchoring of examples, contextualizing, co-membershipping, ‘fishing’ for research collaboration); it also highlights typical patterns of intertextual chaining. The study documents variation in the use of individual mentions by scholars from different disciplines; it also shows that the order in which scholars present influences the chances of their being mentioned by others. A follow-up questionnaire designed to probe how the patterns identified relate to subsequent collaboration shows that the scholars who mentioned others were more likely to maintain contact and co-author with members of their cohort. Implications of the study for a better understanding of the dynamics of research collaboration and for training for academic practice are briefly discussed

Couples Coping with Li-Fraumeni Syndrome: A Mixed-Methods Study of Family Strengths

Using mixed methodology involving qualitative and quantitative data, this dissertation fills gaps in knowledge regarding psychosocial implications for families living with the genetically-transmitted Li-Fraumeni cancer susceptibility syndrome, specifically targeting couple dyads. An initial review of the existing literature on couples coping with heritable cancer syndromes identified gaps in knowledge, and pointed to future directions for research in this area. The three papers that comprise this dissertation provide multiple perspectives on the levels of distress, coping styles, and social support patterns of couples in which one partner is at high risk of cancer. The first paper investigates spousal distress and coping styles in relation to cancer worry for individuals with Li-Fraumeni Syndrome, using quantitative data from one of the largest existing collections of Li-Fraumeni Syndrome cases. The second paper identifies couples’ coping and communication processes regarding cancer stressors, using semi-structured qualitative interviews of individuals with Li-Fraumeni Syndrome and their partners. The third paper utilizes a social network approach to illustrate shared patterns of emotional, tangible, and informational support that couples report accessing. The integrated findings from these three studies indicate that these subjects are low in general distress but high in cancer-specific worry. Couples cope with this worry by balancing multiple roles, exercising flexibility in family dynamics, and utilizing extensive social support networks. This research provides significant information that can aid in development of effective interventions for couples as they face their ongoing threat of cancer. Recommendations for clinical work with this population include an integrated blend of couple therapy, genetic counseling, and oncology practice that is sensitive to the unique needs of individuals with heritable cancer syndromes and their partners

Dynamics of supply chain relationships: A qualitative study of logistics triads

In recent years, a growing number of organizations have outsourced logistics services to logistics services providers (LSPs). Consequently, the outcome of logistics outsourcing is significant in determining the outcome of contemporary supply chains. To account for greater interconnection between organizations, supply chain relationship is crucial for achieving successful logistics outsourcing. Because organizations need to continuously change their decision-making in outsourcing, relationships among organizations in outsourcing are dynamic. Further, because logistics outsourcing has created more SCRs among suppliers, LSPs, and customers, managers need to use a network perspective to manage multiple relationships in the process of outsourcing. The triadic relationship is recognized as the smallest network structure. Researchers have therefore suggested that studying triadic relationships can help expand the knowledge of managing network structures in supply chains. As a result, the primary goal of this research is to study dynamics of supply chain relationships in logistics outsourcing from a view of triadic relationship. This relationship is called a logistics triad and consists of a supplier, a logistics service provider (LSP), and their common customer. Balance theory is a theory that was specifically developed for studying triadic relationships. Balance theory has been used in this thesis as a theoretical lens to develop a conceptual framework and research propositions in order to study logistics triads. Because only a few supply chain studies have adopted balance theory so far, there is a lack of a well-designed research instrument to investigate the research target that the present study explores. To rectify this paucity, qualitative research was conducted using multiple case studies to explore why and how a logistics triad transitions between different triadic relationship structures. The present research was carried out in two stages. The first stage collected triadic cases from LSPs. To improve validity and reliability, the second stage used a deductive process to test findings of the first stage by collecting triadic cases from suppliers and customers. Results of the comparison between the two stages provided verified research findings because the two stages exhibited close similarity. In stage one, the findings indicate that balance theory on its own is insufficient to explain the stability and dynamics of logistics triads. This led to the identification of factors that influenced the relationship dynamics in logistics triads. Among these factors, the combined effects of purchasing volumes, resource capability, and focal firm can override influences from other factors to determine stability and dynamics of logistics triads. The influence from the focal firm demonstrates that the supply network model is more useful than balance theory to study logistics triads. Overall, this thesis makes four major contributions to the knowledge of supply chain relationships: developing an integrative model of triadic relationship dynamics, identifying control approaches used by organizations to dominate triads, comparison between balance theory and supply network model, and demonstrating organizations' mediating effects on dyadic relationships within triads

Predictors of knowledge creation performance. A quantitative qualitative comparative study of European doctorandi

Aquesta tesi forma part d'un projecte destinat a predir el rendiment acadèmic dels estudiants de doctorat portat a terme per l'INSOC (International Network on Social Capital and Performance). El grup de recerca INSOC està format per les universitats de Girona (Espanya), Ljubljana (Eslovènia), Giessen (Alemanya) i Ghent (Bèlgica). El primer objectiu d'aquesta tesi és desenvolupar anàlisis quantitatius comparatius sobre el rendiment acadèmic dels estudiants de doctorat entre Espanya, Eslovènia i Alemanya a partir dels resultats individuals del rendiment acadèmic obtinguts de cada una de les universitats. La naturalesa internacional del grup de recerca implica la recerca comparativa. Vam utilitzar variables personal, actitudinals i de xarxa per predir el rendiment. El segon objectiu d'aquesta tesi és entendre de manera qualitativa perquè les variables de xarxa no ajuden quantitativament a predir el rendiment a la universitat de Girona (Espanya). En el capítol 1, definim conceptes relacionats amb el rendiment i donam un llistat de cada una de les variables independents (variables de xarxa, personals i actitudinals), resumint la lliteratura. Finalment, explicam com s'organitzen els estudis de doctorat a cada un dels diferents països. A partir d'aquestes definicions teòriques, en els pròxims capítols, primer presentarem els qüestionaris utilitzats a Espanya, Eslovènia i Alemanya per mesurar aquests diferents tipus de variables. Després, compararem les variables que són relevants per predir el rendiment dels estudiants de doctorat a cada país. Després d'això, fixarem diferents models de regressió per predir el rendiment entre països. En tots aquests models les variables de xarxa fallen a predir el rendiment a la Universitat de Girona. Finalment, utilitzem estudis qualitatius per entendre aquests resultats inesperats. En el capítol 2, expliquem com hem dissenyat i conduït els qüestionaris en els diferents països amb l'objectiu d'explicar el rendiment dels estudiants de doctorat obtinguts a Espanya, Eslovènia i Alemanya. En el capítol 3, cream indicadors comparables però apareixen problemes de comparabilitat en preguntes particulars a Espanya, Eslovènia i Alemanya. En aquest capítol expliquem com utilitzem les variables dels tres països per crear indicadors comparables. Aquest pas és molt important perquè el principal objectiu del grup de recerca INSOC és comparar el rendiment dels estudiants de doctorat entre els diferents països. En el capítol 4 comparem models de regressió obtinguts de predir el rendiment dels estudiants de doctorat a les universitats de Girona (Espanya) i Eslovènia. Les variables són característiques dels grups de recerca dels estudiants de doctorat enteses com una xarxa social egocèntrica, característiques personals i actitudinals dels estudiants de doctorat i algunes carecterístiques dels directors. Vam trobar que les variables de xarxa egocèntriques no predien el rendiment a la Universitat de Girona. En el capítol 5, comparem dades eslovenes, espanyoles i alemnayes, seguint la metodologia del capítol 4. Concluïm que el cas alemany és molt diferent. El poder predictiu de les variables de xarxa no millora. En el capítol 6 el grup de recerca dels estudiants de doctorat és entès com una xarxa duocèntrica (Coromina et al., 2008), amb l'objectiu d'obtendre informació de la relació mútua entre els estudiants i els seus directors i els contactes d'ambdós amb els altres de la xarxa. La inclusió de la xarxa duocèntrica no millora el poder predictiu del model de regressió utilitzant les variales egocèntriques de xarxa. El capítol 7 pretèn entendre perquè les variables de xarxa no predeixen el rendiment a la Universitat de Girona. Utilitzem el mètode mixte, esperant que l'estudi qualitatiu pugui cobrir les raons de perquè la qualitat de la xarxa falla en la qualitat del treball dels estudiants. Per recollir dades per l'estudi qualitatiu utilitzem entrevistes en profunditat.This thesis belongs to a wider project designed to predict PhD students' academic performance carried out by the INSOC (International Network on Social Capital and Performance). The INSOC research group is composed by the universities of Girona (Spain), Ljubljana (Slovenia), Giessen (Germany) and Ghent (Belgium). The first aim of this thesis is to develop quantitative comparative analyses about the PhD students' academic performance across Spain, Slovenia and Germany from the individual academic performance results obtained in each university member. The international nature of the research group implies that we strongly emphasize comparative research. We use together background variables, attitudinal variables and social network variables for predicting performance. The second aim of this thesis is to qualitatively understand why network variables fail to quantitatively predict performance in the University of Girona (Spain). Thus, this thesis fit into the multimethod tradition. In Chapter 1, we define concepts related with performance and we give a list of each of the independent variables (social network, background and attitudinal variables) with a literature summary. Finally, we explain how PhD studies are organaized in the different countries. Drawing from these theoretical explanations, in the next chapters we first present the questionnaires used in Spain, Slovenia and Germany to measure these different types of variables. Then, we compare the variables which are relevant in order to predict PhD student performance in each country. After that, we fit alternative regression models to predict performance across countries. In all these models network variables fail to predict performance in the University of Girona. Finally, we use a qualitative study to understand this unexpected result. In Chapter 2, we explain how we designed and conducted a survey in the different countries with the aim of explaining the PhD students' performance obtained in Spain, Slovenia and Germany. In Chapter 3, we create comparable indicators wherever some comparability problems arose with particular questions in Spain, Slovenia and Germany. In this chapter we explain how we used all three countries' variables in order to create comparable indicators. This step is very important because the main goal of the INSOC research group is to compare the PhD student's performance between the different countries. In Chapter 4 we compare regression models obtained to predict PhD students' academic performance in the universities of Girona (Spain) and Slovenia. Explanatory variables are characteristics of PhD student's research group understood as an egocentered social network, background and attitudinal characteristics of the PhD students and some characteristics of the supervisors. We find that egocentered network variables do not predict performance in the University of Girona. In Chapter 5 we compare the Slovenian, Spanish and German data, following the methodology used in Chapter 4. We conclude that the German case is very different. Predictive power of network variables does not improve. In Chapter 6 the PhD student's research group is understood as a duocentered social network (Coromina et al., 2008), in order to obtain information regarding the mutual relationship between PhD students and their supervisor and the ties of both to their alters in the network. The inclusion of duocentered network variables does not improve the predictive power of the regression model using egocentered network variables. Chapter 7 attempts to understand why networks fail to predict performance in the University of Girona. Using the mixed method approach, we expect that a qualitative study can uncover the reasons why the quality of the networks fails to translate into the quality of the students' work. For data collection in the qualitative research we used in-depth interviews