Patterns of psychological adaptation to divorce

Despite the increase in divorces after a long relationship, this trend remains a neglected research topic. The present contribution seeks to identify patterns of psychological adaptation to divorce after a long-term marriage. Data from a questionnaire study with 308 persons aged 45–65 years, who divorced after having been married for an average of 25 years, are presented. Exploratory latent profile analysis with various well-being outcomes revealed five groups: one with average adapted, one with resilients, and three small groups with seriously affected individuals. Discriminant variables between the groups were personality, time since separation, a new relationship, and financial situation. Age, gender, and length of marriage played a marginal role; satisfaction with the former marriage and initiator status were not relevant.

Patterns of Psychological Adaptation to Spousal Bereavement in Old Age

Background: While the negative effects of spousal bereavement on well-being are well documented in empirical research, the large individual differences in psychological adaptation are still not well understood. Objective: This contribution aims to identify patterns of psychological adaptation to spousal loss in old age and to shed light on the role of intra- and interpersonal resources and contextual factors as discriminant variables among these patterns. Methods: The data stem from a cross-sectional questionnaire study of 402 widowed individuals (228 women, 174 men) aged between 60 and 89 years (mean age 74.41 years), who lost their partner within the last 5 years, and 618 married individuals, who served as controls (312 women, 306 men; mean age 73.82 years). Results: The exploratory latent profile analysis of the well-being outcomes of depressive symptoms, hopelessness, loneliness, life satisfaction and subjective health revealed three different groups in the widowed sample: ‘resilients' (54% of the sample), ‘copers' (39%) and ‘vulnerables' (7%). The most important variables for group allocation were intrapersonal resources - psychological resilience and the Big Five personality traits - but also the quality of the former relationship and how the loss was experienced. Conclusion: Successful adaptation to spousal loss is primarily associated with high scores in psychological resilience and extraversion and low scores in neuroticism. Our results shed light on the variability in psychological adaptation and underline the important role of intrapersonal resources in facing spousal loss in old age.

Symptom-based subtypes of depression and their psychosocial correlates: A person-centered approach focusing on the influence of sex

BACKGROUND: Reducing the complexity of major depressive disorder by symptom-based subtypes constitutes the basis of more specific treatments. To date, few studies have empirically derived symptom subtypes separated by sex, although the impact of sex has been widely accepted in depression research. METHODS: The community-based sample included 373 males and 443 females from the Zurich Program for Sustainable Development of Mental Health Services (ZInEP) manifesting depressive symptoms in the past 12 months. Latent Class Analysis (LCA) was performed separately by sex to extract sex-related depression subtypes. The subtypes were characterized by psychosocial characteristics. RESULTS: Three similar subtypes were found in both sexes: a severe typical subtype (males: 22.8%; females: 35.7%), a severe atypical subtype (males: 17.4%; females: 22.6%), and a moderate subtype (males: 25.2%; females: 41.8%). In males, two additional subgroups were identified: a severe irritable/angry-rejection sensitive (IARS) subtype (30%) comprising the largest group, and a small psychomotor retarded subtype (4%). Males belonging to the severe typical subtype exhibited the lowest masculine gender role orientation, while females of the typical subtype showed more anxiety disorders. The severe atypical subtype was associated with eating disorders in both sexes and with alcohol/drug abuse/dependence in females. In contrast, alcohol/drug abuse/dependence was associated with the severe IARS subtype in males. LIMITATIONS:The study had a cross-sectional design, allowing for no causal inferences. CONCLUSIONS:This study contributes to a better understanding of sex-related depression subtypes, which can be well distinguished on the basis of symptom profiles. This provides the base for future research investigating the etiopathogenesis and effective treatment of the heterogeneous depression disorder.

Trajectories of psychological adaptation to marital breakup after a long-term marriage

While the negative effects of divorce on well-being are well documented in research literature, the large individual differences in psychological adaptation over time are still not well understood. This is especially the case for marital breakup after long-term marriage, which is still a neglected research topic. Against this background, the aim of the present contribution is to shed light on the various trajectories of psychological adaptation to marital breakup after a long-term relationship. Data stem from a longitudinal survey study, which is part of the Swiss National Centre of Competence in Research ‘LIVES – Overcoming vulnerability: life course perspectives’ (funded by the Swiss National Science Foundation). Our analyses are based on results of an exploratory latent profile analysis performed at the first assessment in 2012 among 308 divorced participants aged 45 – 65 years, who divorced after an average of 25 years of marriage (Perrig-Chiello, Hutchison, & Morselli, 2014). Five different groups regarding psychological adaptation to marital breakup (i.e. life satisfaction, depression, hopelessness, subjective health, and mourning) were identified. They were composed of two larger groups of individuals that adapted quite well or very well (“average copers”, n=151 and “resilients”, n=90) and of three smaller groups with major difficulties to adjust to the new situation (“vulnerables”, n= 18; “malcontens”, n= 37 and “resigned ones”, n=12). Clusters differed statistically significant regarding personality variables, time since separation, current relationship status, and financial situation. In the present contribution, we want to investigate the course of adaptation of the five classes two years later by using latent transition analysis. Furthermore, we aim to examine which variables in terms of personality, relationship status, variables of the context of the separation and socio-demographic variables are crucial for change or stability in levels of adaptation in the different classes. The evaluation of the trajectories of adaptation to this critical life event and the identification of variables that enhance the adaptation over time is essential for developing more differentiated measures in counselling as well as intervention techniques in clinical and social services.

Trajectories of psychological adaptation to marital breakup after a long-term marriage

Background: Marital dissolution is known to be among the most stressful life events with long- reaching negative consequences on individuals’ lives. A limitation in research to date is that most studies have focused on the impact of marital disruption on well-being outcomes in younger adults. Furthermore, although population-based studies on divorce document a broad range of negative effects, more fine-grained analyses reveal a large heterogeneity in people’s adjustment, which is still not well understood. Objective: To explore trajectories of psychological adaptation to marital breakup after a long-term marriage, and to examine variables accounting for recovery or chronicity in terms of intrapersonal resources (personality, trait resilience, personal growth), relationship variables (satisfaction with ex- relationship, length of marriage, time since divorce) and socio-demographic variables (age, gender, financial situation). Methods: Latent transition analysis is used to examine the course of psychological adaptation (i.e., depressive symptoms, life satisfaction, hopelessness, mourning and subjective health) to divorce over two years among five profiles of 308 divorcees (mean age: 55.6 years; average duration of former marriage: 23.62 years): Two larger groups of individuals, the one which adapted very well (‘resilients’, 29%), the other quite well (‘average copers’, 49%), and three groups with major difficulties (‘vulnerables’, 6%; ‘malcontents’, 12%; and ‘resigned’, 4%). In a second step the differences among transition patterns were explored on the basis of the distal variables (i.e., intrapersonal resources, relationship variables, socio-demographics). Results: Although the probability of upward changes was higher for those individuals with lower adaptation at time 1, only a small number of individuals made an upward change from the maladapted to the well-adapted groups throughout the two years. The groups of copers and resilients remained stable in their psychological adaption. The most consistent results related to upward changes were intrapersonal resources, namely the NEO personality traits and trait resilience. Conclusion: The majority of individuals divorcing after a long-term marriage adapt successfully over time. Adaptation trajectories depend primarily on intrapersonal resources. However, a minority of divorcees exhibit enduring difficulties. Knowledge about the diversity of these trajectories of vulnerability could be of great help for designing psychological interventions to better tackle this critical life event.

Serum Testosterone Levels and Symptom-Based Depression Subtypes in Men

The main objective of this preliminary study was to further clarify the association between testosterone (T) levels and depression by investigating symptom-based depression subtypes in a sample of 64 men. The data were taken from the ZInEP epidemiology survey. Gonadal hormones of a melancholic (n  = 25) and an atypical (n = 14) depression subtype, derived from latent class analysis, were compared with those of healthy controls (n  = 18). Serum T was assayed using an enzyme-linked immunosorbent assay procedure. Analysis of variance, analysis of covariance, non-parametrical tests, and generalized linear regression models were performed to examine group differences. The atypical depressive subtype showed significantly lower T levels compared with the melancholic depressives. While accumulative evidence indicates that, beyond psychosocial characteristics, the melancholic and atypical depressive subtypes are also distinguishable by biological correlates, the current study expanded this knowledge to include gonadal hormones. Further longitudinal research is warranted to disclose causality by linking the multiple processes in pathogenesis of depression.

Career adaptability profiles and their relationship to adaptivity and adapting

Research on career adaptability predominantly uses variable-centered approaches that focus on the average effects in terms of the predictors and outcomes within a given sample. Extending this research, the present paper used a person-centered approach to determine whether subgroups with distinct adaptability profiles in terms of concern, control, curiosity and confidence can be identified. We also explored the relationship between the various adaptability profiles and adapting (career planning, career decision-making difficulties, career exploration, and occupational self-efficacy beliefs) and adaptivity (core self-evaluations and proactivity). Using latent profile analysis, we found distinct adaptability profiles among 350 German university students. Students with different profiles differed significantly in their levels of adapting. This finding was confirmed in a second study of 1226 students selected from the same population. In both samples, the adaptability profiles differed mainly in terms of their adaptability levels but not their shape. Moreover, in both samples, the students whose profiles indicated generally higher adaptability showed more adapting compared with the students whose profiles indicated generally lower adaptability. Study 2 also showed that students with higher-adaptability profiles showed significantly higher adaptivity. The results suggest that level effects dominate adaptability profiles, implying the existence of a general adaptability factor within university students that is meaningfully related to adapting and adaptivity.

HIV prevalence and contextual risk-factors among injection drug users in Harris County, Texas

Injection drug use is the third most frequent risk factor for new HIV infections in the United States. A dual mode of exposure: unsafe drug using practices and risky sexual behaviors underlies injection drug users' (IDUs) risk for HIV infection. This research study aims to characterize patterns of drug use and sexual behaviors and to examine the social contexts associated with risk behaviors among a sample of injection drug users. ^ This cross-sectional study includes 523 eligible injection drug users from Houston, Texas, recruited into the 2009 National HIV Behavioral Surveillance project. Three separate set of analyses were carried out. First, using latent class analysis (LCA) and maximum likelihood we identified classes of behavior describing levels of HIV risk, from nine drug and sexual behaviors. Second, eight separate multivariable regression models were built to examine the odds of reporting a given risk behavior. We constructed the most parsimonious multivariable model using a manual backward stepwise process. Third, we examined whether HIV serostatus knowledge (self-reported positive, negative, or unknown serostatus) is associated with drug use and sexual HIV risk behaviors. ^ Participants were mostly male, older, and non-Hispanic Black. Forty-two percent of our sample had behaviors putting them at high risk, 25% at moderate risk, and 33% at low risk for HIV infection. Individuals in the High-risk group had the highest probability of risky behaviors, categorized as almost always sharing needles (0.93), seldom using condoms (0.10), reporting recent exchange sex partners (0.90), and practicing anal sex (0.34). We observed that unsafe injecting practices were associated with high risk sexual behaviors. IDUs who shared needles had higher odds of having anal sex (OR=2.89, 95%CI: 1.69-4.92) and unprotected sex (OR=2.66, 95%CI: 1.38-5.10) at last sex. Additionally, homelessness was associated with needle sharing (OR=2.24, 95% CI: 1.34-3.76) and cocaine use was associated with multiple sex partners (OR=1.82, 95% CI: 1.07-3.11). Furthermore, twenty-one percent of the sample was unaware of their HIV serostatus. The three groups were not different from each other in terms of drug-use behaviors: always using a new sterile needle, or in sharing needles or drug preparation equipment. However, IDUs unaware of their HIV serostatus were 33% more likely to report having more than three sexual partners in the past 12 months; 45% more likely to report to have unprotected sex and 85% more likely to use drug and or alcohol during or before at last sex compared to HIV-positive IDUs. ^ This analysis underscores the merit of LCA approach to empirically categorize injection drug users into distinct classes and identify their risk pattern using multiple indicators and our results show considerable overlap of high risk sexual and drug use behaviors among the high-risk class members. The observed clustering pattern of drug and sexual risk behavior among this population confirms that injection drug users do not represent a homogeneous population in terms of HIV risk. These findings will help develop tailored prevention programs.^

Decision evaluation in complex risk network systems (DecernsSDSS) demo and Black River case study

The selection of metrics for ecosystem restoration programs is critical for improving the quality of monitoring programs and characterizing project success. Moreover it is oftentimes very difficult to balance the importance of multiple ecological, social, and economical metrics. Metric selection process is a complex and must simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. We propose multicriteria decision analysis (MCDA) methods, broadly defined, for the selection of optimal sets of metrics to enhance evaluation of ecosystem restoration alternatives. Two MCDA methods, a multiattribute utility analysis (MAUT), and a probabilistic multicriteria acceptability analysis (ProMAA), are applied and compared for a hypothetical case study of a river restoration involving multiple stakeholders. Overall, the MCDA results in a systematic, unbiased, and transparent solution, informing restoration alternatives evaluation. The two methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criteria, it is suggested as the best option if data uncertainty is high. Despite the increase in complexity in the metric selection process, MCDA improves upon the current ad-hoc decision practice based on the consultations with stakeholders and experts, and encourages transparent and quantitative aggregation of data and judgement, increasing the transparency of decision making in restoration projects. We believe that MCDA can enhance the overall sustainability of ecosystem by enhancing both ecological and societal needs.

Cross-Lingual Linking of News Stories using ESA

In this paper, we describe our approach for Cross-Lingual linking of Indian news stories, submitted for Cross-Lingual Indian News Story Search (CL!NSS) task at FIRE 2012. Our approach consists of two major steps, the reduction of search space by using di�erent features and ranking of the news stories according to their relatedness scores. Our approach uses Wikipedia-based Cross-Lingual Explicit Semantic Analysis (CLESA) to calculate the semantic similarity and relatedness score between two news stories in di�erent languages. We evaluate our approach on CL!NSS dataset, which consists of 50 news stories in English and 50K news stories in Hindi.

Distributed static linear Gaussian models using consensus

Algorithms for distributed agreement are a powerful means for formulating distributed versions of existing centralized algorithms. We present a toolkit for this task and show how it can be used systematically to design fully distributed algorithms for static linear Gaussian models, including principal component analysis, factor analysis, and probabilistic principal component analysis. These algorithms do not rely on a fusion center, require only low-volume local (1-hop neighborhood) communications, and are thus efficient, scalable, and robust. We show how they are also guaranteed to asymptotically converge to the same solution as the corresponding existing centralized algorithms. Finally, we illustrate the functioning of our algorithms on two examples, and examine the inherent cost-performance tradeoff.

Desarrollo de un entorno inteligente en el contexto del hogar digital

A lo largo de las últimas décadas el desarrollo de la tecnología en muy distintas áreas ha sido vertiginoso. Su propagación a todos los aspectos de nuestro día a día parece casi inevitable y la electrónica de consumo ha invadido nuestros hogares. No obstante, parece que la domótica no ha alcanzado el grado de integración que cabía esperar hace apenas una década. Es cierto que los dispositivos autónomos y con un cierto grado de inteligencia están abriéndose paso de manera independiente, pero el hogar digital, como sistema capaz de abarcar y automatizar grandes conjuntos de elementos de una vivienda (gestión energética, seguridad, bienestar, etc.) no ha conseguido extenderse al hogar medio. Esta falta de integración no se debe a la ausencia de tecnología, ni mucho menos, y numerosos son los estudios y proyectos surgidos en esta dirección. Sin embargo, no ha sido hasta hace unos pocos años que las instituciones y grandes compañías han comenzado a prestar verdadero interés en este campo. Parece que estamos a punto de experimentar un nuevo cambio en nuestra forma de vida, concretamente en la manera en la que interactuamos con nuestro hogar y las comodidades e información que este nos puede proporcionar. En esa corriente se desarrolla este Proyecto Fin de Grado, con el objetivo de aportar un nuevo enfoque a la manera de integrar los diferentes dispositivos del hogar digital con la inteligencia artificial y, lo que es más importante, al modo en el que el usuario interactúa con su vivienda. Más concretamente, se pretende desarrollar un sistema capaz de tomar decisiones acordes al contexto y a las preferencias del usuario. A través de la utilización de diferentes tecnologías se dotará al hogar digital de cierta autonomía a la hora de decidir qué acciones debe llevar a cabo sobre los dispositivos que contiene, todo ello mediante la interpretación de órdenes procedentes del usuario (expresadas de manera coloquial) y el estudio del contexto que envuelve al instante de ejecución. Para la interacción entre el usuario y el hogar digital se desarrollará una aplicación móvil mediante la cual podrá expresar (de manera conversacional) las órdenes que quiera dar al sistema, el cual intervendrá en la conversación y llevará a cabo las acciones oportunas. Para todo ello, el sistema hará principalmente uso de ontologías, análisis semántico, redes bayesianas, UPnP y Android. Se combinará información procedente del usuario, de los sensores y de fuentes externas para determinar, a través de las citadas tecnologías, cuál es la operación que debe realizarse para satisfacer las necesidades del usuario. En definitiva, el objetivo final de este proyecto es diseñar e implementar un sistema innovador que se salga de la corriente actual de interacción mediante botones, menús y formularios a los que estamos tan acostumbrados, y que permita al usuario, en cierto modo, hablar con su vivienda y expresarle sus necesidades, haciendo a la tecnología un poco más transparente y cercana y aproximándonos un poco más a ese concepto de hogar inteligente que imaginábamos a finales del siglo XX. ABSTRACT. Over the last decades the development of technology in very different areas has happened incredibly fast. Its propagation to all aspects of our daily activities seems to be inevitable and the electronic devices have invaded our homes. Nevertheless, home automation has not reached the integration point that it was supposed to just a few decades ago. It is true that some autonomic and relatively intelligent devices are emerging, but the digital home as a system able to control a large set of elements from a house (energy management, security, welfare, etc.) is not present yet in the average home. That lack of integration is not due to the absence of technology and, in fact, there are a lot of investigations and projects focused on this field. However, the institutions and big companies have not shown enough interest in home automation until just a few years ago. It seems that, finally, we are about to experiment another change in our lifestyle and how we interact with our home and the information and facilities it can provide. This Final Degree Project is developed as part of this trend, with the goal of providing a new approach to the way the system could integrate the home devices with the artificial intelligence and, mainly, to the way the user interacts with his house. More specifically, this project aims to develop a system able to make decisions, taking into account the context and the user preferences. Through the use of several technologies and approaches, the system will be able to decide which actions it should perform based on the order interpretation (expressed colloquially) and the context analysis. A mobile application will be developed to enable the user-home interaction. The user will be able to express his orders colloquially though out a conversational mode, and the system will also participate in the conversation, performing the required actions. For providing all this features, the system will mainly use ontologies, semantic analysis, Bayesian networks, UPnP and Android. Information from the user, the sensors and external sources will be combined to determine, through the use of these technologies, which is the operation that the system should perform to meet the needs of the user. In short, the final goal of this project is to design and implement an innovative system, away from the current trend of buttons, menus and forms. In a way, the user will be able to talk to his home and express his needs, experiencing a technology closer to the people and getting a little closer to that concept of digital home that we imagined in the late twentieth century.

Modelo de análisis organizativo para la mejora del desempeño de empresas sociales

La empresa social es un modelo organizativo que presenta un interesante potencial para resolver problemáticas sociales. La empresa social ha despertado interés tanto en países industrializados como en economías en vías de desarrollo porque representa un modelo dentro del capitalismo que persigue objetivos sociales mediante la realización de actividades de mercado (compra y venta de productos y/o servicios principalmente). A pesar de sus raíces lejanas en el tiempo se trata de un campo de conocimiento relativamente joven, donde la literatura académica presenta escasez de estudios empíricos. El desarrollo teórico para buscar claridad conceptual ha sido el principal caballo de batalla de los últimos años, y por tanto, se ha prestado poca atención a generar evidencias sobre cómo funcionan las empresas sociales y sobre sus claves de su éxito. Se considera que la mejora en la comprensión de este modelo organizativo pasa por la construcción de herramientas para que académicos y practicantes mejoren su conocimiento sobre los mecanismos internos de las empresas sociales. En este contexto nace la presente tesis doctoral sobre empresa social, que tiene por objetivo la creación de un marco de análisis que permita el estudio de las empresas sociales desde una dimensión organizativa, es decir, que aborde los elementos clave que describen el funcionamiento de este tipo de organizaciones. Para ello, en este trabajo se aborda la construcción del modelo para el análisis organizativo de las empresas sociales a partir del análisis semántico de las 45 principales definiciones de empresa social. A partir de este análisis se identifican dos dimensiones de análisis de la empresa social: -Cuatro principios, comunes a todas las manifestaciones del fenómeno, que recogen la esencia del concepto. -Ocho elementos organizativos específicos de la empresa social que describen la forma en la que cada iniciativa se implementa en un contexto determinado. Es decir, elementos de diseño presentes en diferente medida que dan lugar a tipologías de empresa social diferentes. Estos elementos son: la proposición de valor social, la búsqueda de impacto a largo plazo, la cultura organizativa, la conexión con los beneficiarios, el liderazgo emprendedor y los mecanismos de gobernanza, el ecosistema colaborativo, la estrategia empresarial y la orientación a la autosuficiencia económica. A partir de este marco de análisis, se construyen dos herramientas de diagnóstico que permiten su aplicación al estudio de empresas sociales: una tabla de indicadores para el análisis externo (por parte de un investigador ajeno a la organización) y un cuestionario de diagnóstico para el análisis interno (a través del personal de la empresa social objeto de estudio). Las herramientas intentan dar respuesta a la necesidad de desarrollar constructos para el estudio empírico de las empresas sociales. Para analizar la utilidad del modelo y de las herramientas se llevaron a cabo tres estudios de caso: -La empresa social ACCIONA Microenergía Perú que proporciona energía eléctrica a comunidades rurales aisladas en la región peruana de Cajamarca. -La empresa social Integra-e que propone un mecanismo de inserción socio-laboral en Madrid para jóvenes en riesgo de exclusión a través de la formación en Tecnologías de la Información y la Comunicación (TIC). -Un conjunto de redes de telecentros pertenecientes a la red LAC de la fundación Telecentres.org que proporcionan acceso a servicios de información (Internet entre otros) en diferentes países de Latinoamérica. La aplicación de las herramientas mostró ser útil en los tres estudios de caso para obtener una relación de evidencias con las que analizar la proximidad de una organización al ideal de empresa social. El ejercicio de análisis también resultó interesante como ejercicio reflexivo para las entidades participantes. Los resultados del cuestionario fueron especialmente interesantes en los telecentros de la Fundación Telecentre.org ya que al ser un estudio multicaso se pudo realizar un rico análisis estadístico sobre el funcionamiento de los telecentros y su desempeño. El estudio permitió identificar relaciones interesantes entre los ocho elementos de diseño del modelo propuesto y el desempeño de la organización. En particular, se detectó que para todos los casos estudiados: -La dimensión económica es la componente del desempeño que mayor desafíos plantea. -La existencia de una alta correlación entre el desempeño y siete de los ocho elementos organizativos del modelo. -La importancia de la cultura organizativa como elemento que explica el desempeño global de la organización y la satisfacción de los empleados. El campo de la empresa social presenta importantes retos de futuro, como la claridad conceptual, el desarrollo de estudios empíricos y la medida de su impacto social. El conocimiento de las claves organizativas puede ayudar a diseñar empresas sociales más robustas o a que organizaciones con fines sociales que no se basan en mecanismos de mercado consideren la posibilidad de incorporar éstos en su estrategia. ABSTRACT Social enterprise is an organizational model with a strong potential to help solving social problems. Recently, interest for the model has risen in both industrialized and developing countries because it is organized to achieve altruistic or social goals through market activities (mainly sales of products and services). Despite its historic roots, it is a relatively young field of research, where academic literature has little empirical data to accompany the theoretical development of social enterprise. Conceptual clarification has been the main challenge during the recent years, and there has been little attention given to generate evidence on how social enterprises operate and their keys to success. Progress in empirical study involves the construction of tools for researchers, in order to increase understanding of the internal mechanisms of social enterprises. This thesis aims to create a conceptual framework to study social enterprises from an organizational point of view, by analyzing the key elements that explain the operation and organization of this organizational model. The framework for the organizational analysis of social enterprises was built supported by the semantic analysis of 45 main definitions of social enterprise. The framework is divided into two dimensions: -There are four principles which capture the essence of the social enterprise concept, and are present in the manifestations of cases. -There are eight design elements which help analyze the characteristics of each particular social enterprise initiative: the social value proposition, social impact orientation, organizational culture, links to beneficiaries, entrepreneurial leadership, collaborative ecosystem, entrepreneurial strategy and orientation to economic self-sufficiency. Two diagnostic tools were developed to apply the framework to case studies: a scoreboard of indicators (to be used by the researcher during external analysis of the organization) and a questionnaire (to be answered by the social enterprise staff). The dissertation undertakes the study of three case studies: -ACCIONA Microenergia Peru, a social enterprise that provides electricity to isolated rural communities in the Peruvian region of Cajamarca. -Integra-e, a social enterprise located in Madrid that promotes socioprofessional integration of young people through training in ICT. -A sample of telecenters of the LAC network that provide access to information services (such as Internet) in Latin America. Applying the tools proved to be useful in all three cases, because it helped to obtain evidence to compare the proximity of an organization to an ideal type of social enterprise. In all the cases studied, the economic sustainability proved to be the biggest challenge for the organizations. The application of the questionnaire to the telecenters was especially informative because it was a multicase study which provided a rich statistical analysis on the performance of call centers. The study identified unique relationships between the model elements and the organziation performance. A statistical analysis shows a high correlation between performance and seven organizational elements described in the model. The organizational culture seems to be an important factor in explaining the overall organizational performance and employee satisfaction. The field of social enterprise has significant future challenges -such as conceptual clarity, the development of empirical studies and social impact assessment. A deep understanding of key organizational aspects of social enterprises can help in the design of more robust organizations and to bring success to social-purpose organizations.

RESSIST: a research object-based recommender system

The scientific method is a methodological approach to the process of inquiry { in which empirically grounded theory of nature is constructed and verified [14]. It is a hard, exhaustive and dedicated multi-stage procedure that a researcher must perform to achieve valuable knowledge. Trying to help researchers during this process, a recommender system, intended as a researcher assistant, is designed to provide them useful tools and information for each stage of the procedure. A new similarity measure between research objects and a representational model, based on domain spaces, to handle them in dif ferent levels are created as well as a system to build them from OAI-PMH (and RSS) resources. It tries to represents a sound balance between scientific insight into individual scientific creative processes and technical implementation using innovative technologies in information extraction, document summarization and semantic analysis at a large scale.

Methods and Techniques for Segmentation of Consumers in Social Media

Los medios sociales han revolucionado la manera en la que los consumidores se relacionan entre sí y con las marcas. Las opiniones publicadas en dichos medios tienen un poder de influencia en las decisiones de compra tan importante como las campañas de publicidad. En consecuencia, los profesionales del marketing cada vez dedican mayores esfuerzos e inversión a la obtención de indicadores que permitan medir el estado de salud de las marcas a partir de los contenidos digitales generados por sus consumidores. Dada la naturaleza no estructurada de los contenidos publicados en los medios sociales, la tecnología usada para procesar dichos contenidos ha menudo implementa técnicas de Inteligencia Artificial, tales como algoritmos de procesamiento de lenguaje natural, aprendizaje automático y análisis semántico. Esta tesis, contribuye al estado de la cuestión, con un modelo que permite estructurar e integrar la información publicada en medios sociales, y una serie de técnicas cuyos objetivos son la identificación de consumidores, así como la segmentación psicográfica y sociodemográfica de los mismos. La técnica de identificación de consumidores se basa en la huella digital de los dispositivos que utilizan para navegar por la Web y es tolerante a los cambios que se producen con frecuencia en dicha huella digital. Las técnicas de segmentación psicográfica descritas obtienen la posición en el embudo de compra de los consumidores y permiten clasificar las opiniones en función de una serie de atributos de marketing. Finalmente, las técnicas de segmentación sociodemográfica permiten obtener el lugar de residencia y el género de los consumidores. ABSTRACT Social media has revolutionised the way in which consumers relate to each other and with brands. The opinions published in social media have a power of influencing purchase decisions as important as advertising campaigns. Consequently, marketers are increasing efforts and investments for obtaining indicators to measure brand health from the digital content generated by consumers. Given the unstructured nature of social media contents, the technology used for processing such contents often implements Artificial Intelligence techniques, such as natural language processing, machine learning and semantic analysis algorithms. This thesis contributes to the State of the Art, with a model for structuring and integrating the information posted on social media, and a number of techniques whose objectives are the identification of consumers, as well as their socio-demographic and psychographic segmentation. The consumer identification technique is based on the fingerprint of the devices they use to surf the Web and is tolerant to the changes that occur frequently in such fingerprint. The psychographic profiling techniques described infer the position of consumer in the purchase funnel, and allow to classify the opinions based on a series of marketing attributes. Finally, the socio-demographic profiling techniques allow to obtain the residence and gender of consumers.