Content analysis model to analyze facets of social mission of public library on the Facebook and in the websites

In this paper we present the development and the implementation of a content analysis model for observing aspects relating to the social mission of the public library on Facebook pages and websites. The model is unique and it was developed from the literature. There were designed the four categories for analysis Generate social capital and social cohesion, Consolidate democracy and citizenship, Social and digital inclusion and Fighting illiteracies. The model enabled the collection and the analysis of data applied to a case study consisting of 99 Portuguese public libraries with Facebook page. With this model of content analysis we observed the facets of social mission and we read the actions with social facets on the Facebook page and in the websites of public libraries. At the end we discuss in parallel the results of observation of the Facebook of libraries and the websites. By reading the description of the actions of the social mission, the general conclusion and the most immediate is that 99 public libraries on Facebook and websites rarely publish social character actions, and the results are little satisfying. The Portuguese public libraries highlight substantially the actions in the category Generate social capital and social cohesion.

Bem-estar subjectivo: processos cognitivos e afecto positivo

O presente trabalho de investigação visa aprofundar o campo de estudo no âmbito do Bem-Estar subjetivo. Especificamente, propõe-se apreciar qual o papel do Processamento Cognitivo "Aberto" (e outras formas de Coping) na relação entre Satisfação com o Suporte Social e o Afecto Positivo e Negativo. A metodologia usada segue um método correlaciona/ quantitativo através do recurso ao software de análise estatística SPSS. As análises de regressão simples e múltipla mostraram que diferentes variáveis, como as cognitivas (Processamento Cognitivo "Aberto" e outras formas de Coping) e os pessoais e sócio-demográficas (Género e Grau de Escolaridade), se encontram associados aos níveis de Afecto, quer Positivo quer Negativo, e contribuem também de formas distintas para explicar a sua variabilidade. Para além disso, as mesmas relações parecem ser influenciadas pelos níveis de Saúde Mental dos participantes. Os resultados do presente estudo sugerem importantes implicações teóricas e práticas no âmbito da Saúde Mental. /ABSTRACT: This research work aims to deepen the field of study within the framework of Subjective Well-Being. Specifically, it proposes to assess the role of the Broad-Minded Coping (and other forms of Coping) in the relationship between Satisfaction with the Social Support and the Positive and Negative Affect. The methodology used follows a correlative quantitative method through the use of the statistical analysis software SPSS. Multiple and simple regression analyses showed that different variables, such as cognitive (Broad-Minded Coping and other forms of Coping) and personal and socio-demographic data (Gender and Scholarization), are associated with the levels of Affect, either Positive or Negative, and they also contribute differently to explain its variability. ln addition, these relationships seem to be influenced by the participants' Mental Health levels. The results of this study suggest important theoretical and practical implications in the context of Mental Health.

Representing image captions as concept graphs using semantic information

Conceptual interpretation of languages has gathered peak interest in the world of artificial intelligence. The challenge in modeling various complications involved in a language is the main motivation behind our work. Our main focus in this work is to develop conceptual graphical representation for image captions. We have used discourse representation structure to gain semantic information which is further modeled into a graphical structure. The effectiveness of the model is evaluated by a caption based image retrieval system. The image retrieval is performed by computing subgraph based similarity measures. Best retrievals were given an average rating of . ± . out of 4 by a group of 25 human judges. The experiments were performed on a subset of the SBU Captioned Photo Dataset. This purpose of this work is to establish the cognitive sensibility of the approach to caption representations

Representing image captions as concept graphs using semantic information

Conceptual interpretation of languages has gathered peak interest in the world of artificial intelligence. The challenge in modeling various complications involved in a language is the main motivation behind our work. Our main focus in this work is to develop conceptual graphical representation for image captions. We have used discourse representation structure to gain semantic information which is further modeled into a graphical structure. The effectiveness of the model is evaluated by a caption based image retrieval system. The image retrieval is performed by computing subgraph based similarity measures. Best retrievals were given an average rating of . ± . out of 4 by a group of 25 human judges. The experiments were performed on a subset of the SBU Captioned Photo Dataset. This purpose of this work is to establish the cognitive sensibility of the approach to caption representations.