PERCEPÇÃO DE SUPORTE SOCIAL E CONSUMO DE ÁLCOOL EM DESEMPREGADOS

O desemprego tem sido objeto de preocupação no contexto político, econômico e social, uma vez que a população de trabalhadores desempregados enfrenta dificuldades diárias para a obtenção de trabalho/ou emprego, situação que gera intenso sofrimento psíquico e pode repercutir de modo negativo na saúde do trabalhador. Este estudo teve por objetivo investigar a percepção de suporte social e o consumo de álcool em desempregados. Por meio de estudo epidemiológico, quantitativo e transversal constituímos uma amostra de 300 indivíduos, recrutados em uma agência pública em São Bernardo do Campo SP, que capta vagas no mercado e encaminha trabalhadores para recolocação profissional. A amostra resultou em 54,3% pessoas do gênero masculino, com idade média de 29,30, com mínimo de 18 anos e máximo de 56 anos; 67% tinham ensino médio, sendo 50% solteiros, 52% encontravam-se desempregados de um a seis meses, 37% residiam em imóvel próprio, e 37% possuíam renda familiar de um a dois salários mínimos. Foram utilizados três instrumentos auto-aplicáveis para coleta dos dados: a) Questionário de características sócio-demográficas; b) Escala de Percepção de Suporte Social (EPSS); c) Teste para Identificação de Problemas Relacionados ao Uso de Álcool (AUDIT). Os dados coletados foram submetidos ao programa estatístico SPSS, versão 15.0 para Windows que permitiu fazer as correlações entre as variáveis. Os resultados indicaram correlações significativas entre as variáveis: suporte prático e renda; suporte prático e suporte emocional, com idade. Estas correlações sugeriram que os sujeitos apresentavam melhor percepção de suporte prático na medida em que aumentava a renda familiar, e que quanto maior a idade, menor é a percepção do suporte prático e emocional recebido pela rede social. O AUDIT não apontou correlações significativas entre as variáveis estudadas, e 76% da amostra se situou na zona 1 consumo de baixo risco ou abstinência. Não verificamos correlação entre consumo de álcool e desemprego.(AU)

PERCEPÇÃO DE SUPORTE SOCIAL E BEM-ESTAR NO TRABALHO: UM ESTUDO COM PROFESSORES

Os estudos sobre as condições de trabalho de profissionais da educação sempre tiveram como objetivo identificar fatores negativos, como o burnout e o estresse. Porém, é sabido que variáveis relacionadas com as relações interpessoais podem proporcionar melhora no bem-estar no trabalho nestes profissionais. O professor, protagonista do processo ensino-aprendizagem pode apresentar bem-estar no trabalho e desempenhar melhor o seu ofício se tiver percepção de suporte daqueles que compõem sua rede social dentro de sua escola. Este trabalho tem como objetivo analisar as relações entre bem-estar no trabalho e percepção de suporte social no trabalho em professores do ensino fundamental. Participaram do estudo 209 professores, do ensino fundamental da rede pública municipal e estadual de ensino, todos do sexo feminino com idade média de 41,55 anos (DP=8,64) e com o nível de instrução mínimo correspondente ao ensino médio. Esses professores responderam a um questionário auto aplicável contendo quatro medidas: Escala de Envolvimento com o Trabalho, Escala de Satisfação com o Trabalho Escala de Comprometimento Organizacional Afetivo e Escala de Percepção de Suporte Social no Trabalho. Calcularam-se as médias, desvios padrão, correlações e sete modelos de regressão linear stepwise entre as variáveis do estudo. Os resultados apontaram para satisfação com os colegas, com a chefia e com as tarefas, mas pouca satisfação com salários e promoções. Os professores apresentaram comprometimento afetivo com suas escolas e envolvimento com o trabalho que realizam. Foi revelada percepção de suporte social, com uma tendência mais elevada de suporte com as informações recebidas, seguida da percepção de suporte emocional e percepção de suporte instrumental nesta ordem. Foram comprovadas relações positivas e significativas entre as dimensões de bem-estar no trabalho e percepção de suporte social no trabalho. Modelos de regressão revelaram que as três dimensões de suporte social no trabalho impactam positivamente as três dimensões de bem-estar no trabalho, com maior capacidade de explicação entre si. Sugere-se novos estudos envolvendo percepção de suporte social no trabalho e bem-estar no trabalho com outras categorias profissionais para complementar estes ainda pouco estudados conceitos.(AU)

Autochthonous heritage languages and social media:writing and bilingual practices in Low German on Facebook

This article analyses how speakers of an autochthonous heritage language (AHL) make use of digital media, through the example of Low German, a regional language used by a decreasing number of speakers mainly in northern Germany. The focus of the analysis is on Web 2.0 and its interactive potential for individual speakers. The study therefore examines linguistic practices on the social network site Facebook, with special emphasis on language choice, bilingual practices and writing in the autochthonous heritage language. The findings suggest that social network sites such as Facebook have the potential to provide new mediatized spaces for speakers of an AHL that can instigate sociolinguistic change.

Feature analysis of spammers in social networks with active honeypots:a case study of Chinese microblogging networks

In this poster we presented our preliminary work on the study of spammer detection and analysis with 50 active honeypot profiles implemented on Weibo.com and QQ.com microblogging networks. We picked out spammers from legitimate users by manually checking every captured user's microblogs content. We built a spammer dataset for each social network community using these spammer accounts and a legitimate user dataset as well. We analyzed several features of the two user classes and made a comparison on these features, which were found to be useful to distinguish spammers from legitimate users. The followings are several initial observations from our analysis on the features of spammers captured on Weibo.com and QQ.com. ¦The following/follower ratio of spammers is usually higher than legitimate users. They tend to follow a large amount of users in order to gain popularity but always have relatively few followers. ¦There exists a big gap between the average numbers of microblogs posted per day from these two classes. On Weibo.com, spammers post quite a lot microblogs every day, which is much more than legitimate users do; while on QQ.com spammers post far less microblogs than legitimate users. This is mainly due to the different strategies taken by spammers on these two platforms. ¦More spammers choose a cautious spam posting pattern. They mix spam microblogs with ordinary ones so that they can avoid the anti-spam mechanisms taken by the service providers. ¦Aggressive spammers are more likely to be detected so they tend to have a shorter life while cautious spammers can live much longer and have a deeper influence on the network. The latter kind of spammers may become the trend of social network spammer. © 2012 IEEE.

Understanding supply chain disruption risk with the aid of social networks and information flows analysis

Supply Chain Risk Management (SCRM) has become a popular area of research and study in recent years. This can be highlighted by the number of peer reviewed articles that have appeared in academic literature. This coupled with the realisation by companies that SCRM strategies are required to mitigate the risks that they face, makes for challenging research questions in the field of risk management. The challenge that companies face today is not only to identify the types of risks that they face, but also to assess the indicators of risk that face them. This will allow them to mitigate that risk before any disruption to the supply chain occurs. The use of social network theory can aid in the identification of disruption risk. This thesis proposes the combination of social networks, behavioural risk indicators and information management, to uniquely identify disruption risk. The propositions that were developed from the literature review and exploratory case study in the aerospace OEM, in this thesis are:- By improving information flows, through the use of social networks, we can identify supply chain disruption risk. - The management of information to identify supply chain disruption risk can be explored using push and pull concepts. The propositions were further explored through four focus group sessions, two within the OEM and two within an academic setting. The literature review conducted by the researcher did not find any studies that have evaluated supply chain disruption risk management in terms of social network analysis or information management studies. The evaluation of SCRM using these methods is thought to be a unique way of understanding the issues in SCRM that practitioners face today in the aerospace industry.

Who you are or whom you know? Consumption interdependences in social networks

This paper presents an analysis of whether a consumer's decision to switch from one mobile phone provider to another is driven by individual consumer characteristics or by actions of other consumers in her social network. Such consumption interdependences are estimated using a unique dataset, which contains transaction data based on anonymized call records from a large European mobile phone carrier to approximate a consumer's social network. Results show that network effects have an important impact on consumers' switching decisions: switching decisions are interdependent between consumers who interact with each other and this interdependence increases in the closeness between two consumers as measured by the calling data. In other words, if a subscriber switches carriers, she is also affecting the switching probabilities of other individuals in her social circle. The paper argues that such an approach is of high relevance to both switching of providers and to the adoption of new products. © 2013 Copyright Taylor and Francis Group, LLC.

Social Recommendation Based on Content and Trust

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

Analysis and identification of spamming behaviors in Sina Weibo microblog

Spamming has been a widespread problem for social networks. In recent years there is an increasing interest in the analysis of anti-spamming for microblogs, such as Twitter. In this paper we present a systematic research on the analysis of spamming in Sina Weibo platform, which is currently a dominant microblogging service provider in China. Our research objectives are to understand the specific spamming behaviors in Sina Weibo and find approaches to identify and block spammers in Sina Weibo based on spamming behavior classifiers. To start with the analysis of spamming behaviors we devise several effective methods to collect a large set of spammer samples, including uses of proactive honeypots and crawlers, keywords based searching and buying spammer samples directly from online merchants. We processed the database associated with these spammer samples and interestingly we found three representative spamming behaviors: Aggressive advertising, repeated duplicate reposting and aggressive following. We extract various features and compare the behaviors of spammers and legitimate users with regard to these features. It is found that spamming behaviors and normal behaviors have distinct characteristics. Based on these findings we design an automatic online spammer identification system. Through tests with real data it is demonstrated that the system can effectively detect the spamming behaviors and identify spammers in Sina Weibo.

Connecting social media to e-commerce:cold-start product recommendation using microblogging information

In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation, which aims to recommend products from e-commerce websites to users at social networking sites in 'cold-start' situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users' social networking features to another feature representation for product recommendation. In specific, we propose learning both users' and products' feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users' social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.

The network structure of Hungarian business clusters

This article investigates the attitudes to inter-firm co-operation in Hungary by analysing a special group of business networks: the business clusters. Following an overview of cluster policy, a wide range of selfproclaimed business clusters are identified. A small elite of these business networks evolves into successful, sustainable innovative business clusters. However, in the majority of cases, these consortia of interfirm co-operation are not based on a mutually satisfactory model, and as a consequence, many clusters do not survive in the longer term. The paper uses the concepts and models of social network theory in order to explain, why and under what circumstances inter-firm co-operation in clusters enhances the competitiveness of the network as a whole, or alternatively, under what circumstances the cluster remains dependent on Government subsidies. The empirical basis of the study is a thorough internet research about the Hungarian cluster movement; a questionnaire based expert survey among managers of clusters and member companies and a set of in-depth interviews among managers of self-proclaimed clusters. The last chapter analyises the applicability of social network theory in the analysis of business networks and a model involving the value chain is recommended.

Late adolescents in transition: Social networks, parent relations, and well -being

A two-year longitudinal study was conducted to investigate late adolescents in transition. An initial investigation with senior high school students assessed students prior to leaving home for college and after college entrance. Of the original 131 participants recontacted two years after their graduation, 78 returned surveys. The study (a) explored changes in social network structure and function, (b) determined whether late adolescent-parent-peer relations change over time, and (c) identified prospectively the impact of social support, adolescent-parent-peer relations, and attachment security on well-being and feelings about the transition after high school. Students attending college locally reported an increase in total network support at Time 2. Regardless of location, more support from friends was received after the transition from high school, whereas family support did not vary across time. Parent relations were closer after the transition and were predictive of various well-being measures and feelings about the transition from high school. ^

Labeling large scale social media data using budget-driven One-class SVM classification

The social media classification problems draw more and more attention in the past few years. With the rapid development of Internet and the popularity of computers, there is astronomical amount of information in the social network (social media platforms). The datasets are generally large scale and are often corrupted by noise. The presence of noise in training set has strong impact on the performance of supervised learning (classification) techniques. A budget-driven One-class SVM approach is presented in this thesis that is suitable for large scale social media data classification. Our approach is based on an existing online One-class SVM learning algorithm, referred as STOCS (Self-Tuning One-Class SVM) algorithm. To justify our choice, we first analyze the noise-resilient ability of STOCS using synthetic data. The experiments suggest that STOCS is more robust against label noise than several other existing approaches. Next, to handle big data classification problem for social media data, we introduce several budget driven features, which allow the algorithm to be trained within limited time and under limited memory requirement. Besides, the resulting algorithm can be easily adapted to changes in dynamic data with minimal computational cost. Compared with two state-of-the-art approaches, Lib-Linear and kNN, our approach is shown to be competitive with lower requirements of memory and time.

Empirical aspects of a mixed method approach to economic network analysis

We discuss the interactions among the various phases of network research design in the context of our current work using Mixed Methods and SNA on networks and rural economic development. We claim that there are very intricate inter-dependencies among the various phases of network research design - from theory and formulation of research questions right through to modes of analysis and interpretation. Through examples drawn from our work we illustrate how choices about methods for Sampling and Data Collection are influenced by these interdependencies.

El consumo tradicional de los nuevos medios. Análisis de la usabilidad de las publicaciones autóctonas para tableta en el contexto universitario español y brasileño

Esta investigación aborda el consumo que los jóvenes universitarios de España y Brasil realizan de las publicaciones para tabletas. A través del estudio de seis casos –las revistas españolas Don, VisàVis y Quality Sport, y los vespertinos brasileños O Globo a Mais, de Río de Janeiro; Estadão Noite, de Sao Paulo; y Diário do Nordeste Plus, de Fortaleza– se aplica una metodología cualitativa, el test de usabilidad, para detectar qué aspectos ralentizan y entorpecen la navegación en las nuevas generaciones de usuarios de medios móviles. A pesar de la influencia de las revistas impresas en la configuración de las publicaciones para tableta, los datos muestran que el usuario necesita “entrenarse” para conocer unas opciones de interacción a veces poco intuitivas o para las que carece de la madurez visual necesaria. Por ello las publicaciones más sencillas obtienen los mejores resultados de usabilidad.

Dificultades del profesorado para planificar, coordinar y evaluar competencias claves. Un análisis desde la Inspección de Educación.

Este artículo presenta una investigación en la que se analizan las dificultades del profesorado para planificar, coordinar y evaluar competencias claves en una muestra de 23 centros educativos. El tema tiene hondas repercusiones ya que una mala praxis educativa de las competencias claves puede conculcar uno de los derechos fundamentales del alumnado a ser evaluado de forma objetiva (LODE: Art.6b y RD 732/1995: Art. 13.1) y poder superar las pruebas de evaluación consideradas necesarias para la obtención del título académico mínimo que otorga el estado español. La investigación se ha desarrollado desde una doble perspectiva metodológica; en primer lugar, es una investigación descriptiva en la que presentamos las características fundamentales de las competencias claves y la normativa básica para su desarrollo y evaluación. En segundo lugar,  aplicamos un procedimiento de análisis con una doble vertiente cualitativa mediante el empleo del programa Atlas-Ti y del enfoque reticular-categorial del análisis de redes sociales con la aplicación de UCINET y el visor yED Graph Editor para abordar el análisis de las principales dificultades y obstáculos detectados. Los resultados muestran que existen serias dificultades en las tres dimensiones analizadas: "planificación", "coordinación" y "evaluación" de competencias clave; especialmente en la necesidad de formación del profesorado, en la evaluación de las competencias, en la metodología para su desarrollo y en los procesos de coordinación interna para su consecución en los centros educativos.