The microstructures of network recall: How social networks are encoded and represented in human memory

AbstractA growing number of studies indicate that aspects of psychology and cognition influence network structure, but much remains to be learned about how network information is stored and retrieved from memory. Are networks recalled as dyads, as triads, or more generally as sub-groups? We employ an experimental design coupled with exponential random graph models to address this issue. We find that respondents flexibly encode social information as triads or groups, depending on the network, but not as dyads. This supports prior research showing that networks are stored using “compression heuristics”, but also provides evidence of cognitive flexibility in the process of encoding relational information

Short-term and long-term stability in electronic communication networks

Network researchers typically focus on patterns of stable relationships, where stability represents the unfolding of social processes over long time frames. By contrast, we argue and empirically demonstrate that social interactions exhibit regularities across different time frames (short and long-term), reflecting distinct social processes

Embeddedness and the Production of Novelty in Music: A Multi-Dimensional Perspective

Creativity and innovation are central to cultural production, but what makes certain producers more likely to innovate than others? We revisit the concept of embeddedness to evaluate how different dimensions of social structure affect the production of novelty in music. Using original data on over 10,000 unique artists and 115,000 songs recorded and released between 1960 and 1995, we estimate how musicians’ social, cultural, organizational, and geographic embeddedness affects their propensity to create novel products. Results from a series of Relational Event Models (REM’s) suggest that artists who are highly culturally and geographically connected are more likely to create novel songs, especially when they span multiple genres, are women, or are in the early stages of their careers. Surprisingly, variations in social and organizational embeddedness do not significantly influence this outcome. These findings produce new insights into the production of novelty in music, and encourage us to further examine the multiplexity of embeddedness and its role in organizing innovation

Time is of the essence: An application of a relational event model for animal social networks.

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

Modeling Relational Events: A Case study on an Open Source Software Project

Sequences of relational events underlie much empirical research on organizational relations. Yet relational event data are typically aggregated and dichotomized to derive networks that can be analyzed with specialized statistical methods. Transforming sequences of relational events into binary network ties entails two main limitations: the loss of information about the order and number of events that compose each tie and the inability to account for compositional changes in the set of actors and/or recipients. In this article, we introduce a newly developed class of statistical models that enables researchers to exploit the full information contained in sequences of relational events. We propose an extension of the models to cater for sequences of relational events linking different sets of actors. We illustrate the empirical application of relational event models in the context of a free/open source software project with the aim to explain the level of effort produced by contributors to the project. We offer guidance in the interpretation of model parameters by characterizing the social processes underlying organizational problem solving. We discuss the applicability of relational events models in organizational research

Time is of the essence: An application of a relational event model for animal social networks.

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

Inter-organizational network influence on long term and short term inter-individual relationships: The Case of a Trade Fair for TV Programs Distribution in Sub-Saharan Africa

International audienceIn this chapter we study the influence of inter-organizational relationships on the formation of inter-individual relationships in the context of a trade fair. From a multilevel network analysis perspective (MNA), research often shows that inter-organizational ties have a strong influence on inter-individual relationship formation and vice-versa. This mutual influence can be seen as a process of adjustment between levels of action that Lazega (Chap. 2 of this volume, and forthcoming) calls “synchronization.” Our study provides insights into specific aspects of this synchronization process. Through the study of a trade fair for TV program distribution in sub-Saharan Africa, we study the influence of inter-organizational ties (deals and partnerships) on short-term-inter-individual relationships created during this ‘field-configuring event’ and on long-term relationships created outside the trade fair but reactivated during the event. We try to understand how this event participates in the formation of a social milieu in which the markets for TV programs in Africa are embedded. We argue that the multilevel influences are different for short-term and long-term inter-individual ties. We assume that inter-organizational networks are more stable than inter-individual networks, since individuals can more easily create and destroy ties. Through our case study, we show that while the inter-organizational contract network influences the long-term inter-individual network, it has a weak influence on the short-term relationships, which supports the idea that synchronization of levels is an important social problem, and that trade fairs are a way either to escape from the constraints that come attached in markets, or a way to manage them

Hepatocellular carcinoma in HIV-infected patients: epidemiological features, clinical presentation and outcome

Objective: Hepatocellular carcinoma (HCC) is an increasing cause of mortality in HIV-seropositive individuals. The aim of the study was to compare the main features of HCC in HIV-seropositive individuals with those in to HIV-negative patients. Patients and methods: All HIV-infected subjects with a diagnosis of HCC included in three cancer registry databases were enrolled in the study as cases. HCC cases that occurred in the province of Brescia, North Italy, in the period 1995–1998 and all cases reported at the Italian Liver Cancer Project were enrolled as controls. All data were collected using a standardized case report form. The main clinical and epidemiological characteristics of patients with HCC and their survival were compared between HIV-positive and uninfected subjects. Results: Forty-one HIV-infected subjects with HCC were identified. Multivariate analysis adjusted for age and sex identified an association between HIV infection and HCV infection [odds ratio (OR), 11; P ¼ 0.005], and infiltrating tumours and/or extranodal metastasis at presentation (OR ¼ 11.8; P , 0.001). HIV infection was independently associated with shorter survival (hazard ratio, 1.63; P ¼ 0.015). Conclusions: HCC in HIV-infected patients is mainly associated with underlying chronic hepatitis C and has a more aggressive clinical course. Thus, preventative strategies (including the treatment of hepatitis C) should be implemented in the management of HIV/HCV-coinfected patients