COMENEGO (Corpus Multilingüe de Economía y Negocios): a metadiscursive analysis approach

This paper describes a stage in the COMENEGO project, which is creating comparable corpora of Business texts in order to distribute them among translation practitioners so that they can use this resource when translating economic, business or financial texts. This stage consists of discursive analysis of a pilot specialised corpus initially compiled in French and Spanish. Its textual resources are classified in different categories which need to be confirmed so that they can be useful when including them into the virtual platform which will allow users exploit the corpus and filter their searches according to their specific needs. The aim of this paper is to propose a discursive analysis approach based on the concept of ‘metadiscourse’ (Hyland, 2005).

EmotiBlog: a model to learn subjective information detection in the new textual genres of the Web 2.0 -a multilingual and multi-genre approach-

Tesis doctoral con mención europea en procesamiento del lenguaje natural realizada en la Universidad de Alicante por Ester Boldrini bajo la dirección del Dr. Patricio Martínez-Barco. El acto de defensa de la tesis tuvo lugar en la Universidad de Alicante el 23 de enero de 2012 ante el tribunal formado por los doctores Manuel Palomar (Universidad de Alicante), Dr. Paloma Moreda (UA), Dr. Mariona Taulé (Universidad de Barcelona), Dr. Horacio Saggion (Universitat Pompeu Fabra) y Dr. Mike Thelwall (University of Wolverhampton). Calificación: Sobresaliente Cum Laude por unanimidad.

Opinion and generic question answering systems: a performance analysis

The importance of the new textual genres such as blogs or forum entries is growing in parallel with the evolution of the Social Web. This paper presents two corpora of blog posts in English and in Spanish, annotated according to the EmotiBlog annotation scheme. Furthermore, we created 20 factual and opinionated questions for each language and also the Gold Standard for their answers in the corpus. The purpose of our work is to study the challenges involved in a mixed fact and opinion question answering setting by comparing the performance of two Question Answering (QA) systems as far as mixed opinion and factual setting is concerned. The first one is open domain, while the second one is opinion-oriented. We evaluate separately the two systems in both languages and propose possible solutions to improve QA systems that have to process mixed questions.

EmotiBlog: a fine-grained model for emotion detection in non-traditional textual genres

This paper presents the first version of EmotiBlog, an annotation scheme for emotions in non-traditional textual genres such as blogs or forums. We collected a corpus composed by blog posts in three languages: English, Spanish and Italian and about three topics of interest. Subsequently, we annotated our collection and carried out the inter-annotator agreement and a ten-fold cross-validation evaluation, obtaining promising results. The main aim of this research is to provide a finer-grained annotation scheme and annotated data that are essential to perform evaluation focused on checking the quality of the created resources.

Machine learning techniques for automatic opinion detection in non-traditional textual genres

This paper presents a preliminary study in which Machine Learning experiments applied to Opinion Mining in blogs have been carried out. We created and annotated a blog corpus in Spanish using EmotiBlog. We evaluated the utility of the features labelled firstly carrying out experiments with combinations of them and secondly using the feature selection techniques, we also deal with several problems, such as the noisy character of the input texts, the small size of the training set, the granularity of the annotation scheme and the language object of our study, Spanish, with less resource than English. We obtained promising results considering that it is a preliminary study.

Evaluating EmotiBlog robustness for sentiment analysis tasks

EmotiBlog is a corpus labelled with the homonymous annotation schema designed for detecting subjectivity in the new textual genres. Preliminary research demonstrated its relevance as a Machine Learning resource to detect opinionated data. In this paper we compare EmotiBlog with the JRC corpus in order to check the EmotiBlog robustness of annotation. For this research we concentrate on its coarse-grained labels. We carry out a deep ML experimentation also with the inclusion of lexical resources. The results obtained show a similarity with the ones obtained with the JRC demonstrating the EmotiBlog validity as a resource for the SA task.

A semantic framework for textual data enrichment

In this work we present a semantic framework suitable of being used as support tool for recommender systems. Our purpose is to use the semantic information provided by a set of integrated resources to enrich texts by conducting different NLP tasks: WSD, domain classification, semantic similarities and sentiment analysis. After obtaining the textual semantic enrichment we would be able to recommend similar content or even to rate texts according to different dimensions. First of all, we describe the main characteristics of the semantic integrated resources with an exhaustive evaluation. Next, we demonstrate the usefulness of our resource in different NLP tasks and campaigns. Moreover, we present a combination of different NLP approaches that provide enough knowledge for being used as support tool for recommender systems. Finally, we illustrate a case of study with information related to movies and TV series to demonstrate that our framework works properly.

Multimodal analysis of a sample of political posters in Ireland during and after the Celtic Tiger

The aim of this research paper is to analyse the key political posters made for the campaigns of Irish political party Fianna Fáil framed in the Celtic Tiger (1997-2008) and post-Celtic Tiger years (2009-2012). I will then focus on the four posters of the candidate in the elections that took place in 1997, 2002, 2007 and 2011 with the intention of observing first how the leader is represented, and later on pinpointing the similarities and possible differences between each. This is important in order to observe the main linguistic and visual strategies used to persuade the audience to vote that party and to highlight the power of the politician. Critical discourse analysis tools will be helpful to identify the main discursive strategies employed to persuade the Irish population to vote in a certain direction. Van Leeuwen’s (2008) social actor theory will facilitate the understanding of how participants are represented in the corpus under analysis. Finally, the main tools of Kress and van Leeuwen’s visual grammar (2006) will be applied for the analysis of the images. The study reveals that politicians are represented in a consistently positive way, with status and formal appearance so that people are persuaded to vote for the party they represent because they trust them as political leaders. The study, thus, points out that the poster is a powerful tool used in election campaigns to highlight the power of political parties.