University of Oviedo

About: University of Oviedo is a education organization based out in Oviedo, Spain. It is known for research contribution in the topics: Population & Catalysis. The organization has 13423 authors who have published 31649 publications receiving 844799 citations. The organization is also known as: Universidá d'Uviéu & Universidad de Oviedo.

The power of prediction with social media

Abstract: – Social media provide an impressive amount of data about users and their interactions, thereby offering computer and social scientists, economists, and statisticians – among others – new opportunities for research. Arguably, one of the most interesting lines of work is that of predicting future events and developments from social media data. However, current work is fragmented and lacks of widely accepted evaluation approaches. Moreover, since the first techniques emerged rather recently, little is known about their overall potential, limitations and general applicability to different domains. Therefore, better understanding the predictive power and limitations of social media is of utmost importance. , – Different types of forecasting models and their adaptation to the special circumstances of social media are analyzed and the most representative research conducted up to date is surveyed. Presentations of current research on techniques, methods, and empirical studies aimed at the prediction of future or current events from social media data are provided. , – A taxonomy of prediction models is introduced, along with their relative advantages and the particular scenarios where they have been applied to. The main areas of prediction that have attracted research so far are described, and the main contributions made by the papers in this special issue are summarized. Finally, it is argued that statistical models seem to be the most fruitful approach to apply to make predictions from social media data. , – This special issue raises important questions to be addressed in the field of social media-based prediction and forecasting, fills some gaps in current research, and outlines future lines of work.

Breast and prostate cancer: an analysis of common epidemiological, genetic, and biochemical features.

Abstract: I. Introduction II. Epidemiological Evidence Associating Breast and Prostate Cancer III. Incidence of Breast and Prostate Cancer in Different Countries: Dietary Factors IV. Genetic Abnormalities Common to Breast and Prostate Cancer A. AR alterations in prostate cancer B. AR alterations in breast cancer C. BRCA1 and BRCA2 alterations in breast cancer D. BRCA1 and BRCA2 alterations in prostate cancer E. Other genes associated with breast or prostate cancer V. Common Biochemical Features of Breast and Prostate Cancer A. Prostate-specific antigen (PSA) B. Apolipoprotein D (apoD) C. Zn-α2-gp D. Gross cystic disease fluid protein-15 E. Pepsinogen C F. Other proteins VI. Growth Factors in Breast and Prostate Cancer A. AIGF B. KGF VII. Theories of Breast and Prostate Cancer Development: Role of Steroid Hormones VIII. Conclusions

Safety management system: Development and validation of a multidimensional scale

Abstract: The literature has recognised that implementing a safety management system is the most efficient way of allocating resources for safety, since it not only improves working conditions, but also positively influences employees’ attitudes and behaviours with regards safety, consequently improving the safety climate. The safety climate and the safety management system are considered basic components of the firm's safety culture in various models. However, the literature has focused more on measuring the safety climate, while few studies have correctly tested the psychometric properties of the instruments used to measure how advanced the firm's safety management system is. This paper reviews the most important works on safety management, with the aim of developing a measurement scale operationalising the safety management system concept, and subsequently calculating its reliability and validity. For this purpose, exploratory factor analyses and confirmatory factor analyses are conducted, using structural equation models, on a sample of 455 Spanish companies. This scale provides organisations with a tool for evaluating their situation with regards safety management, as well as guidance about which areas they must improve if they wish to reduce occupational accidents.