The study of social network dynamics has become an increasingly important component of many disciplines in the social sciences. In the past decade, statistical models and methods have been proposed which permit researchers to draw statistical inference on these dynamics. This thesis builds on one such family of models, the stochastic actor oriented model (SAOM) proposed by Snijders [2001]. Goodness of fit for SAOMs is an area that is only just beginning to be filled in with appropriate methods. This thesis proposes a Mahalanobis distance based, Monte Carlo goodness of fit test that can depend on arbitrary features of the observed network data and covariates. As remediating poor fit can be a difficult process, a modified model distance (MMD) estimator is devised that can help researchers to choose among a set of model elaborations. In practice, panel data is typically used to draw SAOM-based inference. This thesis also proposes a score-type test for time heterogeneity between the waves in the panel that is computationally cheap and fits into a convenient, forward model selecting workflow. Next, this thesis proposes a rigorous method for aggregating so-called relational event data (e.g. emails and phone calls) by extending the SAOM family to a family of hidden Markov models that suppose a latent social network is driving the observed relational events. Finally, this thesis proposes a measurement model for SAOMs inspired by error-in-variables (EiV) models employed in an array of disciplines. Like the relational event aggregation model, the measurement model is a hidden Markov model extension to the SAOM family. These models allow the researcher to specify the form of the mesurement error and buffer against potential attenuating biases and other problems that can arise if the errors are ignored.

The structure of social networks, and people's position within these networks, are important predictors of many individual and group-level outcomes. One type of social networks that is regularly studied are the mutually interdependent relations of friends. This thesis focusses on friendship networks between adolescents in the context of schools. Arguably the most important and consistently found regularities in adolescent friendship networks are i) the tendency of friendships to be mutual, called reciprocity; ii) their tendency to cluster in groups, known as transitivity; and iii) the tendency of friendships to be present between those that are similar to one another, called homophily. Various social theories originating in different disciplines have theoretically proposed and empirically found micro-mechanisms that explain the regular occurrence of these substructures in friendship networks. This thesis introduces a framework of how the relation between these different networks tendencies can be understood. I propose that each of the three network evolution mechanisms can be connected to a type of social situation in which friends interact to form and maintain their friendships. Social situations that are dyadic and only involve two persons are connected to reciprocal friendships. Group-based social situations, on the other hand, are related to transitivity and homophily, where the groups are either defined socially or through common characteristics. Starting from this proposition, I suggest that when two adolescents share one forum for interaction with one another, i.e. they regularly meet within one of the social situations, meeting in additional other situations does not increase the likelihood of a friendship tie existing as much as could be expected from the sum of the effect of meeting in either situation. Consequently, I expect a negative interaction between the different network mechanisms. After a series of empirical analyses that support the outlined reasoning, I use the developed perspective to investigate how the micro-mechanisms contribute differentially to the creation of newly formed friendships and to the maintenance of already existing friendships. Finally, I show how a situational understanding of friendship can be used to differentiate which friendships are most important for social influence and for peer pressure.

Doctorat en Sciences / info:eu-repo/semantics/nonPublished

Social network analysis (SNA) provides tools to examine relationships between people. Text mining (TM) allows capturing the text they produce in Web 2.0 applications, for example, however it neglects their social structure. This paper applies an approach to combine the two methods named "content-based SNA" (CB-SNA). Using the R mailing lists, R-help and R-devel, we show how this combination can be used to describe people's interests and to find out if authors who have similar interests actually communicate. We find that the expected positive relationship between sharing interests and communicating gets stronger as the centrality scores of authors in the communication networks increase. / Series: Research Report Series / Department of Statistics and Mathematics

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Neurodegeneration is a chronic, progressive and debilitating condition that affects majority of the World's elderly population who are at greater risk. Numerous scientific studies suggest that there could be a common underlying molecular mechanism that promotes the degeneration and the subsequent neuronal loss, however so far the progress in this direction is rather limited. Abnormal protein misfoldings, as well as protein plaque formations in the brain, are some of the hallmark characteristic features of neurodegenerative disorders (NDDs). Genetic and environmental factors, oxidative stress, excessive reactive oxygen species formation, mitochondrial dysfunction, energy depletion and autophagy disruption etc. are some of the widely suspected mechanisms that manifest the cognitive, motor and emotional symptoms of these NDDs. Motivated by some molecular traits found in common in several NDDs, network-based systems biology tools and techniques were used in this study to identify critical molecular players and underlying biological processes that are common for Parkinson's, Alzheimer's and Huntington's disease. Utilizing multiple microarray gene expression datasets, several biomolecular networks such as direct interaction, shortest path, and microRNA regulatory networks were constructed and analyzed for each of the disease conditions. The network-based analysis revealed 26 genes of potential interest in Parkinson's, 16 in Alzheimer's and 30 in Huntington's disease. Many new microRNA-target regulatory interactions were identified. For each disorder, several routes for possible disease initiation and protection scenarios were uncovered. A unified neurodegeneration mechanism network was constructed by utilizing the significantly differentially expressed genes found in common in Parkinson's, Alzheimer's and Huntington's microarray datasets. In this integrated network many key molecular partakers and several biological processes that were significantly affected in all three NDDs were uncovered. The integrated network also revealed complex dual-level interactions that occur between disease contributing and protecting entities. Possibilities of microRNA-target interactions were explored and many such pairs of potential interest in NDDs were suggested. Investigating the integrated network mechanism, we have identified several routes for disease initiating, as well as alleviating ones that could be utilized in common for Parkinson's, Alzheimer's and Huntington's disease. Finding such crucial and universal molecular players in addition to maintaining a delicate balance between neurodegeneration promoters and protectors is vital for restoring the homeostasis in the three NDDs.

How accurately people perceive interpersonal relationships, both among others and with themselves, forms the basis of social inferences about the structure of the social environment and one's place in it. Six hypotheses were tested using the cognitive social structures method from social network analysis with five independent but similar student networks from two universities. Results from all networks were meta-analyzed. Participants gave both their self-reported friendship ratings for every alter in their group and also gave their perceptions of the ratings the other member would give. Perception ratings were correlated to self-report ratings for each participant as a measure of accuracy of social network perception. Participants perceived more structural balance than was present in self-reports in four out of five networks and in the meta-analysis, providing evidence for the balance schema. Attachment anxiety correlated negatively with accuracy for one of the networks but was not statistically significant in the meta-analysis. Being located in a tightly-knit subgroup reduced overall network accuracy, consistent with the strength of weak ties (SWT) theory, in one network but not in the meta-analysis. In only one network did participants overestimated how central they were, though not significantly in the meta-analysis. Being more central in the social network was unrelated to accuracy, as was the mean social network distance between perceiver and targets. Results provide meta-analytic support for the balance schema and limited support for attachment, SWT, and egocentric bias in social network perception.

Increased alcohol consumption over time is one of the characteristic symptoms of Alcohol Use Disorder (AUD). The molecular mechanisms underlying this escalation in intake is still the subject of study. However, the mesocortical and mesolimbic dopamine pathways, and the extended amygdala, because of their involvement in reward and reinforcement are believed to play key roles in these behavioral changes. Multiple gene expression studies have shown that alcohol affects the expression of thousands of genes in the brain. The studies discussed in this document use the systems biology technique of co-expression network analysis to attempt to find patterns within genome-wide expression data from two animal models of chronic, high-dose ethanol exposure. These analyses have identified time-dependent and brain-regions specific patterns of expression in C57Bl/6J mice after multiple exposures to intoxicating doses of ethanol and withdrawal. Specifically, they have identified the PFC and HPC as showing long-term ethanol regulation, and identified Let-7 family miRNAs as potential gene expression regulators of chronic ethanol response. Network analysis also indicates neurotransmitter release and neuroimmune response are very correlated to ethanol intake in chronically exposed mice. Examining gene expression response to chronic ethanol exposure across a variable genetic background revealed that, although gene expression response may show conserved patterns, underlying differences in gene expression influence by genetic background may be what truly underlies voluntary ethanol consumption. Finally, combined network analysis of gene expression in the prefrontal cortex (PFC) of mice and macaques following prolonged ethanol exposure demonstrated that neurotransmission, myelination, transcription, cellular respiration, and, possibly, neurovasculature are affected by chronic ethanol across species. Taken together, these studies generate several new hypothesis and areas of future research into the continued study of druggable targets for AUD.

Fisheries straddling or migrating between international maritime boundaries represent a typical case of the tragedy of the commons. Over two dozen Regional Fisheries Management Organisations (RFMOs) have been created to manage these fisheries, which means it also represents a typical case of 'regime complexity' or 'governance architecture'. These literatures recognise that such institutions do not operate independently and therefore institutional functions such as attracting participants, practising their regulatory role, and performing their mandate should be understood as interdependent. This thesis proposes that we study such institutions together with actors and architectures of relations between and among them, which together I term 'governance complexes', by means of a relational approach. This relational approach combines relational theory, which posits the operation of endogenous relational mechanisms alongside exogenous explanations such as institutional design, with network methods that enable structural insights and robust inference that takes into account these interdependencies. The dissertation comprises two main parts that describe and explain the global fisheries governance complex, respectively. The first describes how the governance complex's three main components, states, RFMOs, and states participation in these RFMOs, have evolved. A topological typology utilising key network concepts is proposed and employed to show that the global fisheries governance complex is not fragmenting but becoming more overlapped and nested. The second part explains how this governance complex has evolved in terms of (1) participation, (2) practice, and (3) performance. First, it finds that while states find institutional design features such as an RFMO’s internal organisation attractive, relational mechanisms such as popularity and closure also provide important heuristics for participatory decisions in complex settings. Second, it finds that high levels of organisation also enables higher regulatory activity, but so do relational mechanisms such as coercion or imitation. Third, it proposes the concept of net effectiveness to gauge an institution’s "take-home" performance once its position in the broader governance complex has been taken into account. The result is not only an explanation of the evolution of global fisheries governance but also a developmental step towards an institutional relationalist theory of governance complexes.

Analysis of differences in price, time and distinct measures of accessibility for eské dráhy Abstract The main aim of this thesis is to resolve the issue of accessibility in the passenger rail network of eské dráhy in the Czech Republic. Secondary objectives are the analysis of distance, time availability, and price of passenger rail service. The main sources are the Railway Timetable 2009 and the geographic database Arc R 500. Basic tool for the processing is geographic information system (GIS) with extension Network Analyst. The main aim of the thesis is to provide a database with the values of distance, time availability and price. Secondary aims are to produce partial maps which present various types of accessibility. Part of the results are also the methodology for establishing different kinds of accessibility, the evaluation of methods used, and quality assessment models used in relation to the database and partial results of comparison with the literature. Keywords: transport accessibility, rail transport, network analysis, accessibility, availability of models, Network Analyst