A non-syntactic approach for text sentiment classification with stopwords

The present approach uses stopwords and the gaps that oc- cur between successive stopwords –formed by contentwords– as features for sentiment classification.

Le développement de la compétence argumentative et l'initiation au discours académique

The aim of the paper is to present the specificity of oral argumentative competence in a foreign language and to propose a tentative model of task-based learning of argumentative discourse. It is assumed in the paper that the communicative situation tasks proposed during classes of French as a foreign language in the French Philology Department should contribute to the academic discourse learning. In the paper we present an analysis of two fragments of argumentative situations; the first one concerns the so-called everyday argumentative situation and another one illustrates an argumentative orientation of academic discourse.

La traduction en polonais des textes d'ancien français: une compétence spécifique

This paper is relating a practical experience of teaching Romance philology students the translation from ancient French into Polish. The main scope is a restitution of an ancient text respecting not only the equivalence at the Iexical and syntactical level, but also the discourse structures, such as the linear sequence of events and events related from different points of view: some examples of solving particular problems are discussed. The whole procedure resembles that of translating from Latin, rather than a translation from one modern language to another.

The impact of investor sentiment on stock returns in emerging markets. The case of Central European markets

This is an accepted manuscript of an article published by Taylor & Francis in Eastern European Economics on July 2015, available online: http://dx.doi.org/10.1080/00128775.2015.1079139

Fasciathérapie et identité professionnelle

Tese apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Doutor em Ciências Sociais, especialidade em Psicologia

"Out of sync": The breakdown of economic sentiment cycles in the E.U.

We present empirical evidence about the properties of economic sentiment cycle synchronization for Germany, France and the UK and compare them with the `crisis' countries Italy, Spain, Portugal and Greece. Instead of using output data we prefer to focus on the economic sentiment indicator (ESI), a forward-looking, survey-based variable consistently available from 1985. The cyclical nature of the ESI allows us to analyze the presence or not of synchronicity among country pairs before and after the onset of the financial crisis. Our results show that ESI movements were mostly synchronous before 2008 but they exhibit a breakdown after 2008, with this feature being more prominent in Greece. We also find that, after the political manoeuvring of the past two years, a cycle re-integration or re-synchronization is on the way. An analysis of the evolution of the synchronicity measures indicates that they can potentially be used to identify sudden phase breaks in ESI co-movement and they can offer a signal as to when the EU economies are getting “in” or “out of sync”.

‘Who Ate All the Pride?’:Patriotic Sentiment and English National Football Support.

The growing popularity of English national insignia in international football tournaments has been widely interpreted as evidence of the emergence of a renewed English national consciousness. However, little empirical research has considered how people in England actually understand football support in relation to national identity. Interview data collected around the time of the Euro 2000 and the 2002 World Cup tournaments fail to substantiate the presumption that support for the England football team maps onto claims to patriotic sentiment in any straightforward way. People with far-right political affiliations did generally use national football support to symbolise a general pride in English national identity. However, other people either claimed not to support the England national team precisely because of its associations with nationalism, or else bracketed the domain of football support from more general connotations of English patriotism.

Using Brain Data for Sentiment Analysis

We present the results of exploratory experiments using lexical valence extracted from brain using electroencephalography (EEG) for sentiment analysis. We selected 78 English words (36 for training and 42 for testing), presented as stimuli to 3 English native speakers. EEG signals were recorded from the subjects while they performed a mental imaging task for each word stimulus. Wavelet decomposition was employed to extract EEG features from the time-frequency domain. The extracted features were used as inputs to a sparse multinomial logistic regression (SMLR) classifier for valence classification, after univariate ANOVA feature selection. After mapping EEG signals to sentiment valences, we exploited the lexical polarity extracted from brain data for the prediction of the valence of 12 sentences taken from the SemEval-2007 shared task, and compared it against existing lexical resources.

Improved lexicon-based sentiment analysis for social media analytics

Social media channels, such as Facebook or Twitter, allow for people to express their views and opinions about any public topics. Public sentiment related to future events, such as demonstrations or parades, indicate public attitude and therefore may be applied while trying to estimate the level of disruption and disorder during such events. Consequently, sentiment analysis of social media content may be of interest for different organisations, especially in security and law enforcement sectors. This paper presents a new lexicon-based sentiment analysis algorithm that has been designed with the main focus on real time Twitter content analysis. The algorithm consists of two key components, namely sentiment normalisation and evidence-based combination function, which have been used in order to estimate the intensity of the sentiment rather than positive/negative label and to support the mixed sentiment classification process. Finally, we illustrate a case study examining the relation between negative sentiment of twitter posts related to English Defence League and the level of disorder during the organisation’s related events.