Exploring the dynamics of depressive symptoms and face-to-face interactions with DyNAM
Timon Elmer | ETH Zurich | Switzerland
Depressive symptoms are associated with various social deficits and thus reduced psychosocial functioning. Such deficits potentially contribute to changes in an individual’s social network. Recent studies suggest that individuals with depressive symptoms tend to have fewer friends and become friends with others who have a similar level of depressive symptoms. Similar mechanisms should operate in face-to-face interaction networks. Assessing social interactions directly can improve our understanding of how depressive symptoms affect social embeddedness and thus the reinforcing cycle of social isolation and increase in depressive symptoms. This study investigates how an individual’s level of depressive symptoms affects his/her social interaction ties. The following research questions are explored: (1) Do individuals with higher levels of depressive symptoms have fewer social interactions? (2) Do individuals with higher levels of depressive symptoms prefer interacting in smaller groups? (3) Do individuals interact more frequently with others that have similar levels of depressive symptoms? In particular, we analyze how these patterns change over the course of two days and in dependence on preexisting friendship ties. We do so in a newly formed community of 50 students attending a social event on the first weekend of their studies. Throughout the weekend, students participated in social activities that intended to facilitate social integration. Prior to the event, 48 (96%) of the students administered an online survey assessing social ties within the cohort (e.g., friendship) and depressive symptoms. During the course of the weekend social interactions were assessed using radio frequency identification (RFID) badges. The research questions are investigated Dynamic Network Actor-Oriented Models (DyNAM).
Financial markets as evolving relational systems: Models and preliminary results from a study of European interbank market
Federica Bianchi | Università della Svizzera italiana | Switzerland
We represent financial markets as evolving relational systems. Using data that we collected on one major European regional interbank market, we examine how market structure emerges from sequences of relational events connecting quoters and aggressors – the two main roles that banks assume in financial transactions. We frame the interbank lending market as the institutional interface that regulates exchange across these roles and that allows sellers and buyers of money to coordinate. We show how individual acts of exchange produce and, at the same time, are produced by structured time-ordered sequences of transaction events connecting buyers and sellers. Building on current theoretical understanding of the dynamics of interorganizational relations, and on available empirical evidence we focus our analysis on relational micro-mechanisms that regulate tendencies toward: (i) repeated transactions – or inertia; (ii) reciprocity – or symmetry; (iii) popularity – or centralization of selling; (iv) activity – or centralization of buying activities, and (v) path-shortening – or closure. The study identifies the mechanisms by which dyadic coordination between buyers and suppliers of money is actually achieved, and clarifies how market structure and individual exchange activities are related.
Dynamicity as an innovation indicator in a longitudinal social network
Gloria Álvarez-Hernández | Dubitare/Universidad Carlos III de Madrid | Spain
Very few studies have focused on knowledge sharing networks from a longitudinal social network (LSN) perspective. We aim to expand this literature in the context of diffusion of technological innovation Foster (1986), Rogers (2010) & Valente (2005). This research uses a new methodology that includes a set of dynamicity measures for LSN, developed and described at Uddin, Khan and Piraveenan (2015). More specifically, this allows to compare two or more LSN regardless of their network sizes, the number of interactions or the number of short intervals of the aggregated network.
These dynamicity measures contemplate two types of behavioral patterns that change over time (variations in the position of the network and variations in participation). Both are considered at three different levels: the actor, the total LSN and the short interval level. They are built by using empirical data from a multinational corporation belonging to the ICT industry. Primary data is collected from a virtual Community of Practice composed by 174 engineers that exchanged 918 emails during a period of four and a half years while deploying different telecommunications networks on a worldwide basis. This total period is subdivided into several sub-periods that match periods of innovation adoption (new software and hardware deployment). In addition, we include some measures based on the innovation adoption dates.
The results suggest that there are differences between the network positional and the participation dynamicity. For both measures the trend over the total period is decreasing with peaks at the beginning of each period. As the performance of the technology improves and the number of technology adopters increase, the participation dynamicity seems to follow different patterns depending on the type of actor (innovator/early adopters, vs. followers). Together, these results suggest that in situations of new technology deployment, dynamicity (positional and participatory) should be encouraged to foster greater access to knowledge, something scarce when new technologies are introduced.
Keywords: longitudinal social networks, dynamicity, innovation, innovation models, participation dynamicity, positional dynamicity,
The evolution of professional networks: specialty, prescribing practice, and physician networks
Margeum Kim | Yale University | United States
How do professionals choose network partners? Why do they decide to break existing relationships? How does work environment affect tie creation and dissolution among professionals? By modeling longitudinal network dynamics using the SIENA, we examine tie creation and dissolution among physicians who treat pediatric and adolescent mental health in the United States.
Networks have huge implications on professionals and professions. First, professionals are often introduced to new clients through professional networks. Second, professional relationships are the conduits of new knowledge, technology, and practices. The structure and evolutionary dynamics of professional networks influence the diffusion of information and practices. Finally, professionals derive and maintain their identity through interactions with peers in professional networks. Networks provide and reinforce norms and beliefs that hold professionals together as a cohesive group.
Despite the paramount importance of professional networks, little is known about how they evolve. This study examines what factors may drive the creation and dissolution of ties between professionals. First, we argue that medical specialty is a strong driver of tie creation in physician networks because of intensive within-specialty socialization during education, training, and credentialing processes. Furthermore, physicians need a sense of belongingness to their specialty groups to maintain professional identity. However, homophily in specialty can be less pronounced when work environment necessitates a well-defined division of labor as well as frequent and efficient coordination between different professional groups. We test this possibility by comparing urban and rural networks because rural areas are known to suffer from physician workforce shortage and in turn, requires more efficient care coordination than urban areas.
Second, we examine whether contentious professional practice stimulates tie dissolution in physician networks. We take prescribing antipsychotics in children and adolescents as an example of contentious behavior in our context as the efficacy of antipsychotic medication in children and adolescents is questionable. Treating children and adolescents with antipsychotics has also raised several concerns including adverse effects on metabolic and endocrine systems and brain development. We expect that physicians who disapprove the pediatric use of antipsychotics are likely to break professional relationships if they observe their network partners have engaged in such contentious medical practice.
The expected contributions of this paper are two-fold. First, the results of this study are expected to expand our understanding of dynamic networks by examining a potential asymmetry between the drivers of tie formation and dissolution. Second, we aim to contribute to our understanding of the evolution of professional networks. Because networks are crucial in maintaining and reinforcing professional identities, norms, and work ethics, the evolutionary dynamics of professional networks have a huge implication on the accountability of the professional community.
The Serendipity of Friendship
Zsófia Boda | ETH Zurich | Switzerland
An extensive line of research into the evolution of friendship networks in communities emphasizes the importance of endogenous structural processes, individual characteristics, and meeting opportunities. First, much has been discovered about how endogenous structural processes such as reciprocity or transitivity shape friendship networks, inducing dependencies between network ties. Second, the role of individual characteristics is well-studied: people prefer others similar to them in their sociodemographic, behavioral, and intrapersonal attributes. Third, meeting opportunities for dyads or groups are essential in stimulating friendship formation between individuals.
While structural mechanisms and individual characteristics can be considered more or less stable, at least in an initial period, the quantity and quality of meeting opportunities seems more arbitrary. This is crucial, since even little changes in initial network patterns could lead to significant differences over the evolution of the network. Investigating the randomness in meeting opportunities and its effect on social ties is thus a key to better understand social network dynamics.
Using a unique combination of survey, observational, and experimental methods, our aim is to better explain the long-term role of initial random factors in friendships and dislike relations. For this, we focus on the complete network of over 200 first-year students at a Swiss university starting their studies together at the same department. We investigate network dynamics of the first semester (3 months). Survey data were collected in two different ways. First, detailed surveys, including questions about social ties, individual social background, and personal and behavioral characteristics, were administered three times: during the students’ first week; four weeks later; and during the last week of the semester. Second, mini-questionnaires were sent out 21 times (twice a week), collecting information about students’ interactions with each other. Observational data were collected using RFID-tags, which recorded actual face-to-face interactions during a socializing weekend at the beginning of the semester attended by almost third of the students. An experimental element has also been added to the study design. Three months before the semester started, freshly admitted students had a chance to attend an informal informational event at the university. Part of the event was organized in small groups, for which we randomly sorted students into groups.
Data were analyzed using longitudinal network models. Results show that the initial grouping of students still has an effect on social ties several months months later. This provides evidence that randomness in initial meeting opportunities can indeed strongly influence network evolution.