Bayesian Nonparametrics to Model Content, User, and Latent Structure in Hawkes Processes

Communication in social networks tends to exhibit complex dynamics both in terms of the users involved and the contents exchanged. For example, email exchanges or activities on social media may exhibit reinforcing dynamics, where earlier events trigger follow-up activity through multiple structured latent factors. Such dynamics have been previously represented using models of reinforcement and reciprocation, a canonical example being the Hawkes process (HP). However, previous HP models do not fully capture the rich dynamics of real-world activity. For example, reciprocation may be impacted by the significance and receptivity of the content being communicated, and modeling the content accurately at the individual level may require identification and exploitation of the latent hierarchical structure present among users. Additionally, real-world activity may be driven by multiple latent triggering factors shared by past and future events, with the latent features themselves exhibiting temporal dependency structures. These important characteristics have been largely ignored in previous work. In this dissertation, we address these limitations via three novel Bayesian nonparametric Hawkes process models, where the synergy between Bayesian nonparametric models and Hawkes processes captures the structural and the temporal dynamics of communication in a unified framework. Empirical results demonstrate that our models outperform competing state-of-the-art methods, by more accurately capturing the rich dynamics of the interactions and influences among users and events, and by improving predictions about future event times, user clusters, and latent features in various types of communication activities

The Hawkes Edge Partition Model for Continuous-time Event-based Temporal Networks

We propose a novel probabilistic framework to model continuously generated interaction events data. Our goal is to infer the \emphimplicit community structure underlying the temporal interactions among entities, and also to exploit how the latent structure influence their interaction dynamics. To this end, we model the reciprocating interactions between individuals using mutually-exciting Hawkes processes. The base rate of the Hawkes process for each pair of individuals is built upon the latent representations inferred using the hierarchical gamma process edge partition model (HGaP-EPM). In particular, our model allows the interaction dynamics between each pair of individuals to be modulated by their respective affiliated communities.Moreover, our model can flexibly incorporate the auxiliary individuals’ attributes, or covariates associated with interaction events. Efficient Gibbs sampling and Expectation-Maximization algorithms are developed to perform inference via Pólya-Gamma data augmentation strategy. Experimental results on real-world datasets demonstrate that our model not only achieves competitive performance compared with state-of-the-art methods, but also discovers interpretable latent structure behind the observed temporal interactions

A Connected World: Social Networks and Organizations

This Element synthesizes the current state of research on organizational social networks from its early foundations to contemporary debates. It highlights the characteristics that make the social network perspective distinctive in the organizational research landscape, including its emphasis on structure and outcomes. It covers the main theoretical developments and summarizes the research design questions that organizational researchers face when collecting and analyzing network data. Then, it discusses current debates ranging from agency and structure to network volatility and personality. Finally, the Element envisages future research directions on the role of brokerage for individuals and communities, network cognition, and the importance of past ties. Overall, the Element provides an innovative angle for understanding organizational social networks, engaging in empirical network research, and nurturing further theoretical development on the role of social interactions and connectedness in modern organizations

Isomorphic effects of managerial and directoral career paths

The extensive array of interlocking directorate research remains near-exclusively cross-sectional or comparative cross-sectional in nature. While this has been fruitful in identifying persistent structures of inter-organisational relationships evidence of the impact of these structures on organisational performance or activity has been more limited. This should not be surprising because, by their nature, relationships have strong longitudinal and dynamic qualities that are likely to be difficult to isolate through cross-sectional approaches. Clearly, managerial practice is inevitably strongly conditioned by the specific contingencies of the time and the information available through networks of colleagues and advisers (particularly at board level) at the time. But managerial and directoral capabilities and mental sets are also developed over time, particularly through previous experiences in these roles and the formation of long-lasting 'strong' and 'weak' relationships. This paper tests the influence of three longitudinal dimensions of managers and directors' relationships on a set of indicators of financial performance, drawing from a large dataset of detailing historic board membership of UK firms. It finds evidence of isomorphic processes through these channels and establishes that the longitudinal design considerably enhances the detection of performance effects from directorate interlocks. More broadly, the research has implications for the conception of collective action and the constitution of 'community'

Role competition in Central Asia? Network analysis, role theory and great power regionalism: a framework for analysis

The present thesis develops an analytical framework that rests on three pillars: 1. Network Analysis; 2. Role Theory; 3. Neorealism. These theoretical and analytical approaches have been hitherto disconnected in IR and FPA, despite their potential for synthesis. Through a critical appreciation of each approach, the author highlights their interoperability and reconceptualizes central themes in international relations such as the agency-structure debate, the concept of power, interdependence and institutions, and the security dilemma. It comes to the conclusion that the analysis of real-world phenomena needs to take into account both material and ideational factors, since ideational and material structures are inextricably interlinked in the conduct of foreign policy. The second part of the thesis applies this analytical framework to the regional case of Central Asia, and traces how great powers have engaged in role competition between 2007 and 2022. In an interpretative content analysis, it finds 13 roles conceptualized by the United States and Russia respectively; five of them are the most salient ones. In addition, it explores the roles enacted by the European Union and China. The main finding is that the great powers engage in competitive role-play and reject each other’s role conceptions; create conflicting role expectations; and eventually find themselves in ideational security dilemmas that are partially characterized by capacity-identity gaps. Importantly, the case demonstrates the interdependence of regional subsystems through international feedback loops. Role location processes in the Central Asian network cluster contributed to the deterioration of great power relations – and conflictual great power relations shaped the regional context