In the last years, Deep Learning (DL) has revolutionised the potential of automatic systems that handle Natural Language Processing (NLP) tasks. We have witnessed a tremendous advance in the performance of these systems. Nowadays, we found embedded systems ubiquitously, determining the intent of the text we write, the sentiment of our tweets or our political views, for citing some examples.In this thesis, we proposed several NLP models for addressing tasks that deal with social media text. Concretely, this work is focused mainly on Sentiment Analysis and Personality Recognition tasks. Sentiment Analysis is one of the leading problems in NLP, consists of determining the polarity of a text, and it is a well-known task where the number of resources and models proposed is vast. In contrast, Personality Recognition is a breakthrough task that aims to determine the users' personality using their writing style, but it is more a niche task with fewer resources designed ad-hoc but with great potential.Despite the fact that the principal focus of this work was on the development of Deep Learning models, we have also proposed models based on linguistic resources and classical Machine Learning models. Moreover, in this more straightforward setup, we have explored the nuances of different language devices, such as the impact of emotions in the correct classification of the sentiment expressed in a text.Afterwards, DL models were developed, particularly Convolutional Neural Networks (CNNs), to address previously described tasks. In the case of Personality v • S'ha desenvolupat un marc teòric que permet interpretar xarxes neuronals convolucionals.
The lexicon that coincides with the geographic region formed by the six countries of the American isthmus has not yet been examined as part of a single dialectical area. Our inquiry proposes to analyse and classify the lexical units that are recorded in dialectical dictionaries as a means to answer the question of whether this is a single dialectical area. Through a quantitative and qualitative methodology, we discover that the Central American territory presents two groups according to lexical repertoire. The results demonstrate that the first includes El Salvador, Guatemala, Honduras and Nicaragua, which have a greater number of coinciding words compared to Costa Rica and Panama. Data about the indicators that shed light on etymological origin and lexical-semantic creation, adoption and adaptation to understand the trends followed by each group are also provided. This work contributes to the possibility of considering Central America as a dialectical unit.
The use of Literature in the philosophy shows the paper heuristic, and even constructive, that carries out the imagination sometimes. In this articles three possible uses of the literary thing in the philosophical test are analyzed through: a) examples, b) reconstruction of forms of life and c) literary arguments like departure points for the moral and political philosophy.
Resumen El análisis morfológico del cuento de Juan Rulfo (1996) Anacleto Morones, permite evidenciar y analizar la complejidad de las relaciones humanas incluso si estas se establecen entre seres aparentemente simples o básicos como es el caso de los personajes del cuento. Bien podría decirse-usando la terminología de Saussureque Anacleto Morones (el personaje) es un signo cuyo significado es Lucas Lucatero y cuyo significante se encuentra expresado en las Viejas o mujeres de Amula.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.