A linked data approach to sentiment and emotion analysis of twitter in the financial domain

Sentiment analysis has recently gained popularity in the financial domain thanks to its capability to predict the stock market based on the wisdom of the crowds. Nevertheless, current sentiment indicators are still silos that cannot be combined to get better insight about the mood of different communities. In this article we propose a Linked Data approach for modelling sentiment and emotions about financial entities. We aim at integrating sentiment information from different communities or providers, and complements existing initiatives such as FIBO. The ap- proach has been validated in the semantic annotation of tweets of several stocks in the Spanish stock market, including its sentiment information.

Análisis cualitativo de la relación entrenador-deportista en etapas de formación en baloncesto = Qualitative analysis of the coach-athlete relationship in youth basketball

La relación entrenador-deportista estudia, dentro del ámbito de la psicología social en el deporte, la interacción de los comportamientos, sentimientos y emociones de ambos miembros de la pareja. Se entiende como un proceso en el que antecedentes como la edad, el género o las características esperadas en el otro condicionan el desarrollo de diferentes componentes, los cuales determinan la calidad de la relación, obteniéndose diferentes resultados tanto a nivel deportivo como personal. En la presente tesis se han estudiado 12 relaciones positivas entrenador-deportista en categorías de formación en baloncesto con el objetivo de conocer los condicionantes, componentes, estrategias y resultados de relaciones efectivas. Para ello, se ha realizado un estudio cualitativo, cuya muestra (N=24) se ha seleccionado de manera deliberada discriminando variables como el nivel deportivo del equipo, las características del entrenador, la duración y la calidad de la relación. Las 12 díadas participaban en el máximo nivel de su categoría, tenían una duración mínima de dos temporadas y fueron calificadas como positivas por los entrenadores principales. La investigación se ha llevado a cabo desde la perspectiva holística del fenómeno, teniendo en cuenta tanto el punto de vista del entrenador como el del jugador. Para la recogida de datos se utilizó la entrevista semiestructurada y en profundidad. Los resultados señalan la necesidad de desarrollar estrategias que promuevan y mantengan relaciones de calidad en baloncesto, ya que éstas tienen un alto impacto en el progreso deportivo y personal de los jugadores jóvenes en baloncesto. Entre los condicionantes de la relación entrenador-deportista se ha percibido que las expectativas formadas en los primeros contactos pueden determinar la calidad de la relación. Por otro lado, los componentes dan lugar a resultados como el crecimiento a nivel personal por parte de los jugadores o un mayor rendimiento deportivo, producido en gran medida por la satisfacción y el bienestar psicológico tanto del entrenador como del jugador. Por último, los resultados indican la importancia de adecuar el comportamiento del entrenador a las características propias de los jugadores en cada categoría de formación. ABSTRACT The coach-athlete relationship studies, within the field of social psychology in sport, the interaction of behavior, feelings and emotions in both partners. It is understood as a process in which antecedents such as age, gender or expectations develop different components. The quality of the relationship is determined by these three elements, leading to different results in sport performance as in personal variables. This thesis examined 12 positive coach-athlete rapports in youth basketball teams in order to better understand the determinants, components, strategies and outcomes of effective relationships. A qualitative study has been carried out. The sample (N = 24) is selected deliberately discriminating variables such as the team’s sportive level, coach characteristics, duration and quality of the relationship. Twelve dyads participated at the highest level in its category, had a minimum of two seasons and were rated as positive by head coaches. The research was conducted from a holistic perspective of the phenomenon, taking into account the point of view of both the coach and the player. Indepth semi-structured interview was used for data collection. The results report the need to develop strategies to promote and maintain high quality relationships in basketball, because they have an important impact in sport and personal development of young basketball players. Expectations raised through different impression cues in the first contacts can determine the quality of the relationship. On the other hand, the components lead to results such as players’ personal growth or sport performance, largely produced by the satisfaction and psychological well being of both the coach and the player. Finally, the results indicate the importance of adapting the coach’s behavior to the characteristics of the different stages of young athletes’ development.

Development of a Dashboard for Sentiment Analysis of Football in Twitter based on Web Components and D3.js

This thesis is the result of a project whose objective has been to develop and deploy a dashboard for sentiment analysis of football in Twitter based on web components and D3.js. To do so, a visualisation server has been developed in order to present the data obtained from Twitter and analysed with Senpy. This visualisation server has been developed with Polymer web components and D3.js. Data mining has been done with a pipeline between Twitter, Senpy and ElasticSearch. Luigi have been used in this process because helps building complex pipelines of batch jobs, so it has analysed all tweets and stored them in ElasticSearch. To continue, D3.js has been used to create interactive widgets that make data easily accessible, this widgets will allow the user to interact with them and �filter the most interesting data for him. Polymer web components have been used to make this dashboard according to Google's material design and be able to show dynamic data in widgets. As a result, this project will allow an extensive analysis of the social network, pointing out the influence of players and teams and the emotions and sentiments that emerge in a lapse of time.