Melbourne School of Psychological Sciences - Research Publications

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    Diversity and Community Can Coexist
    Stivala, A ; Robins, G ; Kashima, Y ; Kirley, M (WILEY, 2016-03)
    We examine the (in)compatibility of diversity and sense of community by means of agent-based models based on the well-known Schelling model of residential segregation and Axelrod model of cultural dissemination. We find that diversity and highly clustered social networks, on the assumptions of social tie formation based on spatial proximity and homophily, are incompatible when agent features are immutable, and this holds even for multiple independent features. We include both mutable and immutable features into a model that integrates Schelling and Axelrod models, and we find that even for multiple independent features, diversity and highly clustered social networks can be incompatible on the assumptions of social tie formation based on spatial proximity and homophily. However, this incompatibility breaks down when cultural diversity can be sufficiently large, at which point diversity and clustering need not be negatively correlated. This implies that segregation based on immutable characteristics such as race can possibly be overcome by sufficient similarity on mutable characteristics based on culture, which are subject to a process of social influence, provided a sufficiently large "scope of cultural possibilities" exists.
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    Norm Talk and Human Cooperation: Can We Talk Ourselves Into Cooperation?
    Shank, DB ; Kashima, Y ; Peters, K ; Li, Y ; Robins, G ; Kirley, M (AMER PSYCHOLOGICAL ASSOC, 2019-07)
    Norm talk is verbal communication that explicitly states or implicitly implies a social norm. To investigate its ability to shape cultural dynamics, 2 types of norm talk were examined: injunction, which explicitly states what should be done, and gossip, which implies a norm by stating an action approved or disapproved of by the communicator. In 2 experiments, participants engaged in norm talk in repeated public goods games. Norm talk was found to help sustain cooperation relative to the control condition; immediately after every norm talk opportunity, cooperation spiked, followed by a gradual decline. Despite the macrolevel uniformity in their effects on cooperation, evidence suggests different microlevel mechanisms for the cooperation-enhancing effects of injunction and gossip. A 3rd study confirmed that both injunction and gossip sustain cooperation by making salient the norm of cooperation, but injunction also effects mutual verification of the communicated norm, whereas gossip emphasizes its reputational implications by linking cooperation to status conferral and noncooperation to reputational damage. A 4th experiment provided additional evidence that norm talk was superior to the promise of conditional cooperation in sustaining cooperation. Implications of the findings for cultural dynamics are discussed in terms of how feelings of shared morality, language-based interpersonal communication, and ritualization of norm communication contribute to social regulation. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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    Fast Maximum Likelihood Estimation via Equilibrium Expectation for Large Network Data
    Byshkin, M ; Stivala, A ; Mira, A ; Robins, G ; Lomi, A (NATURE PORTFOLIO, 2018-07-31)
    A major line of contemporary research on complex networks is based on the development of statistical models that specify the local motifs associated with macro-structural properties observed in actual networks. This statistical approach becomes increasingly problematic as network size increases. In the context of current research on efficient estimation of models for large network data sets, we propose a fast algorithm for maximum likelihood estimation (MLE) that affords a significant increase in the size of networks amenable to direct empirical analysis. The algorithm we propose in this paper relies on properties of Markov chains at equilibrium, and for this reason it is called equilibrium expectation (EE). We demonstrate the performance of the EE algorithm in the context of exponential random graph models (ERGMs) a family of statistical models commonly used in empirical research based on network data observed at a single period in time. Thus far, the lack of efficient computational strategies has limited the empirical scope of ERGMs to relatively small networks with a few thousand nodes. The approach we propose allows a dramatic increase in the size of networks that may be analyzed using ERGMs. This is illustrated in an analysis of several biological networks and one social network with 104,103 nodes.
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    Time is of the essence: an application of a relational event model for animal social networks
    Patison, KP ; Quintane, E ; Swain, DL ; Robins, G ; Pattison, P (SPRINGER, 2015-05)
    Understanding how animal social relationships are created, maintained and severed has ecological and evolutionary significance. Animal social relationships are inferred from observations of interactions between animals; the pattern of interaction over time indicates the existence (or absence) of a social relationship. Autonomous behavioural recording technologies are increasingly being used to collect continuous interaction data on animal associations. However, continuous data sequences are typically aggregated to represent a relationship as part of one (or several) pictures of the network of relations among animals, in a way that parallels human social networks. This transformation entails loss of information about interaction timing and sequence, which are particularly important to understand the formation of relationships or their disruption. Here, we describe a new statistical model, termed the relational event model, that enables the analysis of fine-grained animal association data as a continuous time sequence without requiring aggregation of the data. We apply the model to a unique data set of interaction between familiar and unfamiliar steers during a series of 36 experiments to investigate the process of social disruption and relationship formation. We show how the model provides key insights into animal behaviour in terms of relationship building, the integration process of unfamiliar animals and group building dynamics. The relational event model is well suited to data structures that are common to animal behavioural studies and can therefore be applied to a range of social interaction data to understand animal social dynamics.
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    Hepatitis C Transmission and Treatment in Contact Networks of People Who Inject Drugs
    Rolls, DA ; Sacks-Davis, R ; Jenkinson, R ; McBryde, E ; Pattison, P ; Robins, G ; Hellard, M ; Noymer, A (PUBLIC LIBRARY SCIENCE, 2013-11-01)
    Hepatitis C virus (HCV) chronically infects over 180 million people worldwide, with over 350,000 estimated deaths attributed yearly to HCV-related liver diseases. It disproportionally affects people who inject drugs (PWID). Currently there is no preventative vaccine and interventions feature long treatment durations with severe side-effects. Upcoming treatments will improve this situation, making possible large-scale treatment interventions. How these strategies should target HCV-infected PWID remains an important unanswered question. Previous models of HCV have lacked empirically grounded contact models of PWID. Here we report results on HCV transmission and treatment using simulated contact networks generated from an empirically grounded network model using recently developed statistical approaches in social network analysis. Our HCV transmission model is a detailed, stochastic, individual-based model including spontaneously clearing nodes. On transmission we investigate the role of number of contacts and injecting frequency on time to primary infection and the role of spontaneously clearing nodes on incidence rates. On treatment we investigate the effect of nine network-based treatment strategies on chronic prevalence and incidence rates of primary infection and re-infection. Both numbers of contacts and injecting frequency play key roles in reducing time to primary infection. The change from "less-" to "more-frequent" injector is roughly similar to having one additional network contact. Nodes that spontaneously clear their HCV infection have a local effect on infection risk and the total number of such nodes (but not their locations) has a network wide effect on the incidence of both primary and re-infection with HCV. Re-infection plays a large role in the effectiveness of treatment interventions. Strategies that choose PWID and treat all their contacts (analogous to ring vaccination) are most effective in reducing the incidence rates of re-infection and combined infection. A strategy targeting infected PWID with the most contacts (analogous to targeted vaccination) is the least effective.
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    Hepatitis C Virus Phylogenetic Clustering Is Associated with the Social-Injecting Network in a Cohort of People Who Inject Drugs
    Sacks-Davis, R ; Daraganova, G ; Aitken, C ; Higgs, P ; Tracy, L ; Bowden, S ; Jenkinson, R ; Rolls, D ; Pattison, P ; Robins, G ; Grebely, J ; Barry, A ; Hellard, M ; Blackard, J (PUBLIC LIBRARY SCIENCE, 2012-10-26)
    It is hypothesized that social networks facilitate transmission of the hepatitis C virus (HCV). We tested for association between HCV phylogeny and reported injecting relationships using longitudinal data from a social network design study. People who inject drugs were recruited from street drug markets in Melbourne, Australia. Interviews and blood tests took place three monthly (during 2005-2008), with participants asked to nominate up to five injecting partners at each interview. The HCV core region of individual isolates was then sequenced and phylogenetic trees were constructed. Genetic clusters were identified using bootstrapping (cut-off: 70%). An adjusted Jaccard similarity coefficient was used to measure the association between the reported injecting relationships and relationships defined by clustering in the phylogenetic analysis (statistical significance assessed using the quadratic assignment procedure). 402 participants consented to participate; 244 HCV infections were observed in 238 individuals. 26 genetic clusters were identified, with 2-7 infections per cluster. Newly acquired infection (AOR = 2.03, 95% CI: 1.04-3.96, p = 0.037, and HCV genotype 3 (vs. genotype 1, AOR = 2.72, 95% CI: 1.48-4.99) were independent predictors of being in a cluster. 54% of participants whose infections were part of a cluster in the phylogenetic analysis reported injecting with at least one other participant in that cluster during the study. Overall, 16% of participants who were infected at study entry and 40% of participants with newly acquired infections had molecular evidence of related infections with at least one injecting partner. Likely transmission clusters identified in phylogenetic analysis correlated with reported injecting relationships (adjusted Jaccard coefficient: 0.300; p<0.001). This is the first study to show that HCV phylogeny is associated with the injecting network, highlighting the importance of the injecting network in HCV transmission.
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    Comparison of three methods for ascertainment of contact information relevant to respiratory pathogen transmission in encounter networks
    McCaw, JM ; Forbes, K ; Nathan, PM ; Pattison, PE ; Robins, GL ; Nolan, TM ; McVernon, J (BMC, 2010-06-10)
    BACKGROUND: Mathematical models of infection that consider targeted interventions are exquisitely dependent on the assumed mixing patterns of the population. We report on a pilot study designed to assess three different methods (one retrospective, two prospective) for obtaining contact data relevant to the determination of these mixing patterns. METHODS: 65 adults were asked to record their social encounters in each location visited during 6 study days using a novel method whereby a change in physical location of the study participant triggered data entry. Using a cross-over design, all participants recorded encounters on 3 days in a paper diary and 3 days using an electronic recording device (PDA). Participants were randomised to first prospective recording method. RESULTS: Both methods captured more contacts than a pre-study questionnaire, but ascertainment using the paper diary was superior to the PDA (mean difference: 4.52 (95% CI 0.28, 8.77). Paper diaries were found more acceptable to the participants compared with the PDA. Statistical analysis confirms that our results are broadly consistent with those reported from large-scale European based surveys. An association between household size (trend 0.14, 95% CI (0.06, 0.22), P < 0.001) and composition (presence of child 0.37, 95% CI (0.17, 0.56), P < 0.001) and the total number of reported contacts was observed, highlighting the importance of sampling study populations based on household characteristics as well as age. New contacts were still being recorded on the third study day, but compliance had declined, indicating that the optimal number of sample days represents a trade-off between completeness and quality of data for an individual. CONCLUSIONS: The study's location-based reporting design allows greater scope compared to other methods for examining differences in the characteristics of encounters over a range of environments. Improved parameterisation of dynamic transmission models gained from work of this type will aid in the development of more robust decision support tools to assist health policy makers and planners.
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    A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models
    Rolls, DA ; Wang, P ; McBryde, E ; Pattison, P ; Robins, G ; Moreno, Y (PUBLIC LIBRARY SCIENCE, 2015-11-10)
    We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random graph models (ERGMs) and extensions of the configuration model. We use three kinds of empirical contact networks, chosen to provide both variety and realistic patterns of human contact: a highly clustered network, a bipartite network and a snowball sampled network of a "hidden population". In the case of the snowball sampled network we present a novel method for fitting an edge-triangle model. In our results, ERGMs consistently capture clustering as well or better than configuration-type models, but the latter models better capture the node degree distribution. Despite the additional computational requirements to fit ERGMs to empirical networks, the use of ERGMs provides only a slight improvement in the ability of the models to recreate epidemic features of the empirical network in simulated SIR epidemics. Generally, SIR epidemic results from using configuration-type models fall between those from a random network model (i.e., an Erdős-Rényi model) and an ERGM. The addition of subgraphs of size four to edge-triangle type models does improve agreement with the empirical network for smaller densities in clustered networks. Additional subgraphs do not make a noticeable difference in our example, although we would expect the ability to model cliques to be helpful for contact networks exhibiting household structure.
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    Low Carbon Readiness Index: A short measure to predict private low carbon behaviour
    O'Brien, LV ; Meis, J ; Anderson, RC ; Rizio, SM ; Ambrose, M ; Bruce, G ; Critchley, CR ; Dudgeon, P ; Newton, P ; Robins, G ; Kashima, Y (Elsevier, 2018-06-01)
    This paper presents a theoretical argument that low carbon strivings – personal goals to reduce carbon footprint in the household – can predict a wide range of diverse behaviours to reduce greenhouse gas emissions, and reports four studies to validate Low Carbon Readiness Index (LCRI), a short, three-item measure of low carbon strivings. It is a simple and easy-to-use indicator of the general public's readiness to transition to a fully low carbon lifestyle. LCRI is associated with validated measures predicting environmentally significant reported behaviour (Study 1), multiple low carbon behavioural clusters (Study 2 & 3), and predicts reduction in actual energy use, arguably an aggregate measure of actual low carbon behaviours (Study 4). LCRI can be used to develop low carbon policies and monitor their implementation.
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    Influence of Contact Definitions in Assessment of the Relative Importance of Social Settings in Disease Transmission Risk
    Bolton, KJ ; McCaw, JM ; Forbes, K ; Nathan, P ; Robins, G ; Pattison, P ; Nolan, T ; McVernon, J ; Jefferson, T (PUBLIC LIBRARY SCIENCE, 2012-02-16)
    BACKGROUND: Realistic models of disease transmission incorporating complex population heterogeneities require input from quantitative population mixing studies. We use contact diaries to assess the relative importance of social settings in respiratory pathogen spread using three measures of person contact hours (PCH) as proxies for transmission risk with an aim to inform bipartite network models of respiratory pathogen transmission. METHODS AND FINDINGS: Our survey examines the contact behaviour for a convenience sample of 65 adults, with each encounter classified as occurring in a work, retail, home, social, travel or "other" setting. The diary design allows for extraction of PCH-interaction (cumulative time in face-face conversational or touch interaction with contacts)--analogous to the contact measure used in several existing surveys--as well as PCH-setting (product of time spent in setting and number of people present) and PCH-reach (product of time spent in setting and number of people in close proximity). Heterogeneities in day-dependent distribution of risk across settings are analysed using partitioning and cluster analyses and compared between days and contact measures. Although home is typically the highest-risk setting when PCH measures isolate two-way interactions, its relative importance compared to social and work settings may reduce when adopting a more inclusive contact measure that considers the number and duration of potential exposure events. CONCLUSIONS: Heterogeneities in location-dependent contact behaviour as measured by contact diary studies depend on the adopted contact definition. We find that contact measures isolating face-face conversational or touch interactions suggest that contact in the home dominates, whereas more inclusive contact measures indicate that home and work settings may be of higher importance. In the absence of definitive knowledge of the contact required to facilitate transmission of various respiratory pathogens, it is important for surveys to consider alternative contact measures.