Twitter research for social scientists : A brief introduction to the benefits, limitations and tools for analysing Twitter data

The analysis of social media is currently very important due to the unprecedented quantity of information. Twitter is becoming an indispensable source of information for researchers aiming to implement big data in their projects. However, despite the potential eld of research opened by that Twitter data, it contains some risks a researcher must be aware. In this paper I present on the one hand the bene ts and caveats of research conducted on Twitter, and on the other hand the constraints of Twitter data collected from the Application Programming Interfaces (APIs). There are, therefore, three major methodological problems identi ed: (i) representation bias: it is very di cult to make general assumptions using research based on Twitter. (ii) language challenge: users can write in many di erent languages. It implies that when collecting data, some cautions need to be taken in order to accurately gather the data we need, (iii) data bias: Depending of the data needed, one API might be a better t than other. The main aim in this paper is to discuss these methodological constraints from a theoretical point of view. I propose, as a starting point, possible solutions to overcome them, or at least reduce their impact in the research

Lógica difusa aplicada a conjuntos imbalanceados : aplicación a la detección del síndrome de Down /

Consultable des del TDXTítol obtingut de la portada digitalitzadaEl problema a resolver en esta Tesis Doctoral consiste en hallar una solución que mejore la clasificación que se consigue actualmente para el problema de la detección precoz del síndrome de Down en fetos, durante el segundo trimestre de embarazo, con técnicas no invasivas. El conjunto de datos usado para la detección del síndrome de Down es de dos clases y de tipo imbalanceado, es decir, que hay una gran diferencia entre el número de casos correspondientes a fetos que no son afectados por el síndrome de Down y los que sí lo son. Para tratar de mejorar la clasificación que se logra en la actualidad, se ha desarrollado un nuevo método de Soft Computing basado en Lógica Difusa diseñado para trabajar con conjuntos de datos imbalanceados. Este método permite, no sólo hallar una buena solución, sino también extraer el conocimiento adquirido. El método desarrollado se denomina FLAGID (Fuzzy Logic And Genetic algorithms for Imbalanced Datasets) y se basa en la idea de que la solución generalice lo máximo posible, para evitar el efecto de sobreaprendizaje («overfitting») que se produce en la mayoría de métodos al tratar de trabajar con un conjunto de datos imbalanceado. Para proporcionar las herramientas necesarias al método para que generalice, se ha desarrollado un algoritmo llamado ReRecBF, que forma parte del método FLAGID. Este algoritmo transforma las funciones de pertenencia obtenidas a partir de los datos por otro algoritmo ya existente llamado DDA/RecBF. Esta transformación consiste en convertir las funciones de pertenencia generadas a partir de los casos de la clase-menor en funciones triangulares, dejar como funciones trapezoidales las funciones de pertenencia de la clase-mayor y dividir las funciones de pertenencia que se solapen. Finalmente, debido a que se generan nuevas funciones de pertenencia, un algoritmo genético es usado simplemente para hallar las reglas que más se ajusten a las nuevas funciones. Los resultados obtenidos han mejorado la tasa de falsos positivos en el conjunto de datos del síndrome de Down hasta el 4%, con una tasa de verdaderos positivos del 60%. Esta es la primera vez que un método consigue bajar del 5% de falsos positivos con esa tasa de aciertos en los verdaderos positivos. Además, se ha extraído el conocimiento del resultado, y éste ha coincidido, en su mayoría, con el conocimiento existente en el campo de la medicina. Otro hecho remarcable es que se ha comprobado que el método también es útil para trabajar con conjuntos de datos imbalanceados. Finalmente, los resultados de este trabajo realizan aportaciones nuevas en el campo de la medicina, como son la importancia de la edad gestacional del feto en la detección de los casos positivos y que el peso de la madre tiene más importancia que simplemente el calibrar los dos indicadores hormonales AFP y hCG.The problem to solve in this PhD Thesis consists of finding a solution that improves the classification that is obtained at the moment for the problem of the detection of the Down syndrome in fetuses, during the second trimester of pregnancy, with non-invasive techniques. The dataset used for the detection of the Down syndrome is imbalanced and two classes type, that is, that there are a great difference between the number of cases corresponding to fetuses that are not affected by the Down syndrome and those that are affected. In order to try to improve the classification that is obtained at the present time, a new method of Soft Computing has been developed based on Fuzzy Logic and designed to work with imbalanced datasets. This method allows, not only to find a good solution, but also to extract the acquired knowledge. The developed method is called FLAGID (Fuzzy Logic And Genetic algorithms for Imbalanced Datasets) and it is based on the idea that the solution tries to generalize at maximum, avoiding the overfitting effect that takes place in most of methods when trying to work with an imbalanced dataset. In order to provide the necessary tools to the method that allows it to generalize, an algorithm called ReRecBF has been developed, which is a part of method FLAGID. This algorithm transforms the membership functions obtained from the data by another existing algorithm, called DDA/RecBF. This transformation consists of turning the membership functions generated from the cases of the minor-class in triangular functions, leaving like trapezoidal functions the membership functions of the major-class, dividing the membership functions that are overlapped. Finally, because new membership functions are generated, a genetic algorithm is used simply to find the rules that adjust more to the new functions. The results obtained have improved the rate of false positives in the data set of the Down syndrome until 4%, with a rate of true positives of 60%. This is the first time that a method is able to achieve a lower rate of 5% of false positives with that rate of successes in the true positives. In addition, the knowledge of the result has been extracted, and this one has agreed, in its majority, with the existing knowledge in the field of the medicine. Another remarkable fact is that it has been verified that the method also is useful to work with imbalanced datasets. Finally, the results of this work make new contributions in the field of the medicine, like the importance of the gestational age of the fetus in the detection of the positive cases and that the weight of the mother has more indicating importance than simply calibrating both hormonal AFP and hCG

Reactions to Juncker’s State of the Union speech show the difficulties in creating a European public sphere online

Can platforms like Twitter facilitate the creation of a European public sphere? Based on an analysis of tweets during Jean-Claude Juncker’s ‘State of the Union 2016’ speech, Javier Ruiz-Soler outlines how Twitter can be conceived of as a ‘networked public sphere’ in which citizens have the potential to engage in a more democratic and participative form of political conversation. He finds little evidence for a genuine public sphere existing in relation to the speech, but suggests that other topics can generate more heterogeneous networks, with civil society and independent actors playing a greater role

The Last Will Be the First. A Study of European Issue Publics on Twitter

This article analyzes topics of European relevance on Twitter. It does so by examining #schengen and #ttip Twitter hashtags as a case study. The purpose of this article is to detect which accounts are most important in terms of the number of ties received, and whether they are elite or non-elite actors. This is done by calculating the in-degree and out-degree scores of nodes involved in the networks generated by the usage of the two hashtags. The research reveals that it is easier for civil society and citizens to enjoy an important level of attention similar to that of the media, institutions and politicians on topics of European relevance. The outcomes of this research are important when it comes to understanding how a digital platform such as Twitter contributes to bottom-up conversations about relevant European topics. What we learn here about the structure and configuration of these networks helps us obtaining a more fine-grained understanding of new forms of communication and interaction used by citizens, and their implications for the emergence of a European Public Sphere

Volatility Transmission between the stock and Currency Markets in Emerging Asia: the Impact of the Global Financial Crisis

This paper examines volatility spillovers between the stock and currency markets of ten Asian economies in the period 2003 to 2014. To carry out this analysis, a multivariate asymmetric GARCH model is used. In general, our results present evidence of bidirectional volatility spillovers between both markets, independently of the individual country’s level of development. Additionally, our findings show that the global financial crisis has had mixed effects on the volatility transmission patterns. Overall, our results suggest that exchange rate policies and investment decisions should not be implemented without first taking into consideration the links between the stock and currency markets

The doctor-patient relationship in primary healthcare organizations in Spain. A qualitative approach

Antecedentes. La relación médico-paciente es aquella que se produce durante la interacción entre el usuario y el profesional. Esta ha ido cambiando a lo largo de la historia. En la actualidad, el paradigma emergente es el que autonomiza y empodera al usuario, en contraposición al tradicional paradigma paternalista. Objetivo. El objetivo de este trabajo es averiguar el estado del fenómeno sociológico del empoderamiento del paciente en España, desde el punto de vista de los profesionales sanitarios. Metodología. Se realizó un estudio exploratorio mediante una metodología cualitativa. La recolección de datos se basó en entrevistas estructuradas no estandarizadas. Se procedió al análisis del contenido a través de un proceso circular simultáneamente a la recolección de datos. Se complementó con un estudio de fuentes documentales bibliográficas a propósito de la temática abordada. Resultados. Los profesionales muestran una actitud positiva hacia el fenómeno del empoderamiento del paciente. Todavía se muestran escépticos ante la fiabilidad de la información sobre salud que se encuentra en internet y del criterio de los propios pacientes. Aun así, el máximo de autonomía del paciente, el consentimiento informado, sigue siendo considerado como una herramienta de protección del profesional. Discusión. Tras este estudio exploratorio se ha podido observar un cambio de actitud en el profesional respecto a la percepción que tiene sobre la evolución en la relación con el paciente. Se empieza a constatar que el fenómeno social se encuentra en un estado en el que los actores adquieren posturas más simétricas jerárquicamente.Background. The doctor-patient relationship, which happens during the interaction between the user and the professional, has been changing throughout history. The currently emerging paradigm is the one making the user autonomous and empowering him, rather than the traditional paternalistic paradigm. Objective. The objective of this research is to figure out the status of the sociological phenomenon of patient empowerment in Spain, from the vantage point of the healthcare professionals. Methodology. An exploratory study was conducted, using qualitative methodology. Data were gathered based on non-standardized structured interviews. Contents were analyzed through a circular process, at the same time as the data were gathered. This was complemented by a bibliographical documentary sources study with regards to the themes discussed. Results. The professionals show a positive attitude towards the patient empowerment phenomenon. They are still skeptical of the reliability of the health information that can be found on the Internet and of the patient’s own criteria. Even so, the greatest representative of patient autonomy, informed consent, continues to be regarded as a tool for protecting the professional. Discussion. After this exploratory study, it has been possible to observe a change in attitude for the professionals, regarding the perception they have on the evolution of the relationship with patients. It is starting to show that the social phenomenon is at a point where the actors acquire more hierarchically symmetrical positions

Face perception: An integrative review of the role of spatial frequencies

The aim of this article is to reinterpret the results obtained from the research analyzing the role played by spatial frequencies in face perception. Two main working lines have been explored in this body of research: the critical bandwidth of spatial frequencies that allows face recognition to take place (the masking approach), and the role played by different spatial frequencies while the visual percept is being developed (the microgenetic approach). However, results obtained to date are not satisfactory in that no single explanation accounts for all the data obtained from each of the approaches. We propose that the main factor for understanding the role of spatial frequencies in face perception depends on the interaction between the demands of the task and the information in the image (the diagnostic recognition approach). Using this new framework, we review the most significant research carried out since the early 1970s to provide a reinterpretation of the data obtained