[pt] Os transtornos de ansiedade estão entre os transtornos psiquiátricos mais prevalentes em todo o mundo, e achados clínicos apontam para significativa comorbidade entre transtornos de ansiedade e depressão no mesmo indivíduo. Especificamente em relação ao transtorno de ansiedade generalizada (GAD), a comorbidade com depressão em muitos casos está presente. Uma questão de grande preocupação é o impacto desses transtornos nas interações sociais. O estado de tensão e excessivas preocupações exibidas por esses indivíduos podem ser transmitidas para as pessoas de seu convívio social, assim como as interações sociais podem funcionar como um fator ansiogênico para essas pessoas. Ainda existem lacunas a respeito dos mecanismos comportamentais, neurobiológicos e genéticos envolvidos nesses transtornos, e esses aspectos precisam ser investigados. Preocupações com o aumento da prevalência dos transtornos de ansiedade e depressão ressaltam a necessidade de compreender a natureza dual das interações sociais na saúde mental, enfatizando o seu papel como fontes de bem-estar quanto como potenciais estressores. Nosso objetivo é examinar a relação dos transtornos de ansiedade e depressão com o isolamento social. Por meio de uma pesquisa empírica utilizando os ratos Cariocas, um modelo animal de ansiedade selecionado bidirecionalmente para alta e baixa resposta de congelamento condicionado, pretendemos analisar quantitativamente o impacto do isolamento social no comportamento semelhante ao depressivo nessas linhagens (artigo 1). Posteriormente, através de uma análise abrangente da literatura existente, investigamos se o isolamento social alivia os sintomas comuns a esses transtornos, considerando os mecanismos emocionais e cognitivos envolvidos nas interações sociais entre humanos (artigo 2). Para tanto, 72 animais foram divididos nas três linhagens Carioca com alto congelamento condicionado (CAC), Carioca com baixo congelamento condicionado (CBC) e os animais controle (CTR) com níveis intermediários de congelamento. Metade dos animais foram mantidos agrupados de acordo com a respectiva linhagem e a outra metade foi mantida isolada socialmente em gaiolas menores. Posteriormente todos os animais foram submetidos ao teste do nado forçado, tendo seus comportamentos analisados. Na sequência, conforme os dados encontrados, ampliamos nossos estudos através de uma revisão narrativa para compreendermos como esses transtornos psiquiátricos interagem com as relações interpessoais. / [en] Anxiety disorders are among the most prevalent psychiatric disorders worldwide, and clinical findings indicate significant comorbidity between anxiety disorders and depression in the same individual. Specifically concerning generalized anxiety disorder (GAD), comorbidity with depression is often present. A major concern is the impact of these disorders on social interactions. The state of tension and excessive worry exhibited by these individuals can be transmitted to those in their social circles, while social interactions can also serve as an anxiety provoking factor for them. There are still gaps in understanding the behavioral, neurobiological, and genetic mechanisms involved in these disorders, and these aspects need to be investigated. Concerns about the rising prevalence of anxiety and depression disorders underscore the necessity of understanding the dual nature of social interactions in mental health, highlighting their role as sources of well-being as well as potential stressors. Our aim is to examine the relationship between anxiety disorders and depression with social isolation. Through empirical research using Carioca rats, a bidirectionally selected animal model of anxiety with high and low conditioned freezing responses, we intend to quantitatively analyze the impact of social isolation on depression-like behavior in these strains (Article 1). Subsequently, through a comprehensive review of existing literature, we will investigate whether social isolation alleviates symptoms associated with these disorders, taking into account the emotional and cognitive mechanisms involved in social interactions among humans (Article 2). To this end, 72 animals were divided into three strains: Carioca with high conditioned freezing (CAC), Carioca with low conditioned freezing (CBC), and control animals (CTR) with intermediate freezing levels. Half of the animals were maintained in groups according to their respective lineage, while the other half were kept in socially isolated conditions within smaller cages. Subsequently, all animals were subjected to the forced swim test, where their behaviors were analyzed. Following the findings, we expanded our studies through a narrative review to understand how these psychiatric disorders interact with interpersonal relationships.

The availability and scale of user generated data in online systems raises tremendous challenges and opportunities to analytic study of human activities. Effective modeling of online human activities is not only fundamental to the understanding of human behavior, but also important to the online industry. This thesis focuses on developing models and algorithms to predict human activities in online systems and to improve the algorithmic design of personalized/socialized systems (e.g., recommendation, advertising, Web search systems). We are particularly interested in three types of online user activities, i.e., decision making, social interactions and user-generated contents. Centered around these activities, the thesis focuses on three challenging topics: 1. Behavior prediction, i.e., predicting users' online decisions. We present Collaborative-Competitive Filtering, a novel game-theoretic framework for predicting users' online decision making behavior and leverage the knowledge to optimize the design of online systems (e.g., recommendation systems) in respect of certain strategic goals (e.g., sales revenue, consumption diversity). 2. Social contagion, i.e., modeling the interplay between social interactions and individual behavior of decision making. We establish the joint Friendship-Interest Propagation model and the Behavior-Relation Interplay model, a series of statistical approaches to characterize the behavior of individual user's decision making, the interactions among socially connected users, and the interplay between these two activities. These techniques are demonstrated by applications to social behavior targeting. 3. Content mining, i.e., understanding user generated contents. We propose the Topic-Adapted Latent Dirichlet Allocation model, a probabilistic model for identifying a user's hidden cognitive aspects (e.g., knowledgability) from the texts created by the user. The model is successfully applied to address the challenge of ``language gap" in medical information retrieval.